Object memory data flow instruction execution

ABSTRACT

Embodiments of the invention provide systems and methods for managing processing, memory, storage, network, and cloud computing to significantly improve the efficiency and performance of processing nodes. More specifically, embodiments of the present invention are directed to an instruction set of an object memory fabric. This object memory fabric instruction set can be used to provide a unique instruction model based on triggers defined in metadata of the memory objects. This model represents a dynamic dataflow method of execution in which processes are performed based on actual dependencies of the memory objects. This provides a high degree of memory and execution parallelism which in turn provides tolerance of variations in access delays between memory objects. In this model, sequences of instructions are executed and managed based on data access. These sequences can be of arbitrary length but short sequences are more efficient and provide greater parallelism.

CROSS-REFERENCE TO RELATED APPLICATIONS

The present application claims benefit under 35 USC 119(e) of U.S.Provisional Application No. 62/105,549, filed on Jan. 20, 2015 by Franket al and entitled “Infinite Memory Fabric Instruction Set,” of whichthe entire disclosure is incorporated herein by reference for allpurposes.

The present application is also related to the following co-pending andcommonly assigned U.S. Patent Applications:

U.S. patent application Ser. No. 15/001,320 filed Jan. 20, 2016 by Frankand entitled “Object Based Memory Fabric;”

U.S. patent application Ser. No. 15/001,332 filed Jan. 20, 2016 by Frankand entitled “Trans-Cloud Object Based Memory;”

U.S. patent application Ser. No. 15/001,340 filed Jan. 20, 2016 by Frankand entitled “Universal Single Level Object Memory Address Space;”

U.S. patent application Ser. No. 15/001,343 filed Jan. 20, 2016 by Frankand entitled “Object Memory Fabric Performance Acceleration;”

U.S. patent application Ser. No. 15/001,451 filed Jan. 20, 2016 by Frankand entitled “Distributed Index for Fault Tolerance Object MemoryFabric;”

U.S. patent application Ser. No. 15/001,494 filed Jan. 20, 2016 by Frankand entitled “Implementation of an Object Memory Centric Cloud;”

U.S. patent application Ser. No. 15/001,524 filed Jan. 20, 2016 by Frankand entitled “Managing Meta-Data in an Object Memory Fabric;”

U.S. patent application Ser. No. 15/001,652 filed Jan. 20, 2016 by Frankand entitled “Utilization of a Distributed Index to Provide ObjectMemory Fabric Coherency;”

U.S. patent application Ser. No. 15/001,490 filed Jan. 20, 2016 by Frankand entitled “Object Memory Data Flow Triggers;” and

U.S. patent application Ser. No. 15/001,526 filed Jan. 20, 2016 by Frankand entitled “Object Memory Instruction Set,” of which the entiredisclosure of each is incorporated herein by reference for all purposes.

BACKGROUND OF THE INVENTION

Embodiments of the present invention relate generally to methods andsystems for improving performance of processing nodes in a fabric andmore particularly to changing the way in which processing, memory,storage, network, and cloud computing, are managed to significantlyimprove the efficiency and performance of commodity hardware.

As the size and complexity of data and the processes performed thereoncontinually increases, computer hardware is challenged to meet thesedemands. Current commodity hardware and software solutions fromestablished server, network and storage providers are unable to meet thedemands of Cloud Computing and Big Data environments. This is due, atleast in part, to the way in which processing, memory, and storage aremanaged by those systems. Specifically, processing is separated frommemory which is turn is separated from storage in current systems andeach of processing, memory, and storage is managed separately bysoftware. Each server and other computing device (referred to herein asa node) is in turn separated from other nodes by a physical computernetwork, managed separately by software and in turn the separateprocessing, memory, and storage associated with each node are managed bysoftware on that node.

FIG. 1 is a block diagram illustrating an example of the separation datastorage, memory, and processing within prior art commodity servers andnetwork components. This example illustrates a system 100 in whichcommodity servers 105 and 110 are communicatively coupled with eachother via a physical network 115 and network software 155 as known inthe art. Also as known in the art, the servers can each execute anynumber of one or more applications 120 a, 120 b, 120 c of any variety.As known in the art, each application 120 a, 120 b, 120 c executes on aprocessor (not shown) and memory (not shown) of the server 105 and 110using data stored in physical storage 150. Each server 105 and 110maintains a directory 125 mapping the location of the data used by theapplications 120 a, 120 b, 120 c. Additionally, each server implementsfor each executing application 120 a, 120 b, 120 c a software stackwhich includes an application representation 130 of the data, a databaserepresentation 135, a file system representation 140, and a storagerepresentation 145.

While effective, there are three reasons that such implementations oncurrent commodity hardware and software solutions from establishedserver, network and storage providers are unable to meet the increasingdemands of Cloud Computing and Big Data environments. One reason for theshortcomings of these implementations is their complexity. The softwarestack must be in place and every application must manage the separationof storage, memory, and processing as well as applying parallel serverresources. Each application must trade-off algorithm parallelism, dataorganization and data movement which is extremely challenging to getcorrect, let alone considerations of performance and economics. Thistends to lead to implementation of more batch oriented solutions in theapplications, rather than the integrated real-time solutions preferredby most businesses. Additionally, separation of storage, memory, andprocessing, in such implementations also creates significantinefficiency for each layer of the software stack to find, move, andaccess a block of data due to the required instruction execution andlatencies of each layer of the software stack and between the layers.Furthermore, this inefficiency limits the economic scaling possible andlimits the data-size for all but the most extremely parallel algorithms.The reason for the latter is that the efficiency with which servers(processors or threads) can interact limits the amount of parallelismdue to Amdahl's law. Hence, there is a need for improved methods andsystems for managing processing, memory, and storage to significantlyimprove the performance of processing nodes.

BRIEF SUMMARY OF THE INVENTION

Embodiments of the invention provide systems and methods for managingprocessing, memory, storage, network, and cloud computing tosignificantly improve the efficiency and performance of processingnodes. More specifically, embodiments of the present invention aredirected to an instruction set of an object memory fabric. This objectmemory fabric instruction set can be used to provide a uniqueinstruction model based on triggers defined in metadata of the memoryobjects. This model represents a dynamic dataflow method of execution inwhich processes are performed based on actual dependencies of the memoryobjects. This provides a high degree of memory and execution parallelismwhich in turn provides tolerance of variations in access delays betweenmemory objects. In this model, sequences of instructions are executedand managed based on data access. These sequences can be of arbitrarylength but short sequences are more efficient and provide greaterparallelism.

According to one embodiment, a hardware-based processing node of anobject memory fabric can comprise a memory module storing and managingone or more memory objects. Each memory object can be created nativelywithin the memory module, can be accessed using a single memoryreference instruction without Input/Output (I/O) instructions, and canbe managed by the memory module at a single memory layer using a set ofmetadata defined for each memory object and according to a memory dataflow model. Sequences of instructions can be executed and managed basedon access of data of one or more of the memory objects. The sequences ofinstructions can be defined in the object metadata and the objectmetadata can be local to each memory object.

The object memory fabric can comprise a plurality of hardware-basedprocessing nodes and each memory object and the metadata of each memoryobject can be maintained on any one or more of the plurality of nodes inthe object memory fabric. In such cases, managing the memory objectsaccording to the memory data flow model can include executing thesequences of instructions local to each memory object as the memoryobjects are moved, split, or duplicated between nodes. Each sequence ofinstructions can have a corresponding thread state and wherein thethread state for each sequence of instructions is stored in the metadatafor the memory object. The sequences of instructions can be executed andmanaged based on actual dependencies of the memory objects.

In some cases, the hardware-based processing node can comprise a DualIn-line Memory Module (DIMM) card. For example, the hardware-basedprocessing node can comprise a commodity server and the memory modulecan comprise a Dual In-line Memory Module (DIMM) card installed withinthe commodity server. A communication interface can also be coupled withthe object memory fabric. For example, the communication interfacecomprises a Peripheral Component Interconnect Express (PCI-e) card. Inother cases, the hardware-based processing node can comprise a mobilecomputing device. In yet another example, the hardware-based processingnode can comprise a single chip.

According to one embodiment, an object memory fabric can comprise aplurality of hardware-based processing nodes. Each hardware-basedprocessing node can comprise one or more memory modules storing andmanaging one or more memory objects, wherein each memory object iscreated natively within the memory module, each memory object isaccessed using a single memory reference instruction withoutInput/Output (I/O) instructions, and each memory object is managed bythe memory module at a single memory layer using a set of metadatadefined for each memory object and according to a memory data flowmodel. Each hardware-based processing node can also comprise a noderouter communicatively coupled with each of the one or more memorymodules of the node and adapted to route memory objects or portions ofmemory objects between the one or more memory modules of the node. Theobject memory fabric can further comprise one or more inter-node routerscommunicatively coupled with each node router, wherein each of theplurality of nodes of the object memory fabric is communicativelycoupled with at least one of the inter-node routers and adapted to routememory objects or portions of memory objects between the plurality ofnodes.

In such an object memory fabric, sequences of instructions can beexecuted and managed based on access of data of one or more of thememory objects. The sequences of instructions can be defined in theobject metadata and the object metadata can be local to each memoryobject. Each memory object and the metadata of each memory object can bemaintained on any one or more of the plurality of nodes in the objectmemory fabric and managing the memory objects according to the memorydata flow model can include executing the sequences of instructionslocal to each memory object as the memory objects are moved, split, orduplicated between nodes. Each sequence of instructions can have acorresponding thread state and the thread state for each sequence ofinstructions can be stored in the metadata for the memory object. Thesequences of instructions can also be executed and managed based onactual dependencies of the memory objects. In some implementations, atleast one hardware-based processing node can comprise a commodityserver, the one or more memory modules of the commodity server cancomprise at least one Dual In-line Memory Module (DIMM) card installedwithin the commodity server. In such cases, the communication interfacecan comprise a Peripheral Component Interconnect Express (PCI-e) card.Additionally or alternatively, at least one hardware-based processingnode can comprise a mobile computing device, a single chip, and/or otherform factor.

According to yet another embodiment, a method for storing and managingone or more memory objects in an object memory fabric can comprisecreating each memory object natively within a memory module of ahardware-based processing node of the object memory fabric, accessingeach memory object using a single memory reference instruction withoutInput/Output (I/O) instructions, and managing each memory object withinthe memory module at a single memory layer using a set of metadatadefined for each memory object and according to a memory data flowmodel. Sequences of instructions can be executed and managed based onaccess of data of one or more of the memory objects. The sequences ofinstructions can be defined in the object metadata and the objectmetadata can be local to each memory object. The object memory fabriccan comprise a plurality of hardware-based processing nodes and eachmemory object and the metadata of each memory object can be maintainedon any one or more of the plurality of nodes in the object memoryfabric. Managing the memory objects according to the memory data flowmodel can include executing the sequences of instructions local to eachmemory object as the memory objects are moved, split, or duplicatedbetween nodes. Each sequence of instructions can have a correspondingthread state and the thread state for each sequence of instructions canbe stored in the metadata for the memory object. The sequences ofinstructions can also be executed and managed based on actualdependencies of the memory objects.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a block diagram illustrating an example of the separation datastorage, memory, processing, network, and cloud computing within priorart commodity servers and network components.

FIG. 2 is a block diagram illustrating components of an exemplarydistributed system in which various embodiments of the present inventionmay be implemented.

FIG. 3 is a block diagram illustrating an exemplary computer system inwhich embodiments of the present invention may be implemented.

FIG. 4 is a block diagram illustrating an exemplary object memory fabricarchitecture according to one embodiment of the present invention.

FIG. 5 is a block diagram illustrating an exemplary memory fabric objectmemory according to one embodiment of the present invention.

FIG. 6 is a block diagram illustrating an exemplary object memorydynamics and physical organization according to one embodiment of thepresent invention.

FIG. 7 is a block diagram illustrating aspects of object memory fabrichierarchy of object memory, which localizes working sets and allows forvirtually unlimited scalability, according to one embodiment of thepresent invention.

FIG. 8 is a block diagram illustrating aspects of an examplerelationship between object address space, virtual address, and physicaladdress, according to one embodiment of the present invention.

FIG. 9 is a block diagram illustrating aspects of an examplerelationship between object sizes and object address space pointers,according to one embodiment of the present invention.

FIG. 10 is a block diagram illustrating aspects of an example objectmemory fabric distributed object memory and index structure, accordingto one embodiment of the present invention.

FIG. 11 illustrates aspects of an object memory hit case that executescompletely within the object memory, according to one embodiment of thepresent invention.

FIG. 12 illustrates aspects of an object memory miss case and thedistributed nature of the object memory and object index, according toone embodiment of the present invention.

FIG. 13 is a block diagram illustrating aspects of an example of leaflevel object memory in view of the object memory fabric distributedobject memory and index structure, according to one embodiment of thepresent invention.

FIG. 14 is a block diagram illustrating aspects of an example of objectmemory fabric router object index structure, according to one embodimentof the present invention.

FIGS. 15A and 15B are block diagrams illustrating aspects of exampleindex tree structures, including node index tree structure and leafindex tree, according to one embodiment of the present invention.

FIG. 16 is a block diagram illustrating aspects of an example physicalmemory organization, according to one embodiment of the presentinvention.

FIG. 17A is a block diagram illustrating aspects of example objectaddressing, according to one embodiment of the present invention.

FIG. 17B is a block diagram illustrating aspects of example objectmemory fabric pointer and block addressing, according to one embodimentof the present invention.

FIG. 18 is a block diagram illustrating aspects of example objectmetadata, according to one embodiment of the present invention.

FIG. 19 is a block diagram illustrating aspects of an examplemicro-thread model, according to one embodiment of the presentinvention.

FIG. 20 is a block diagram illustrating aspects of an examplerelationship of code, frame, and object, according to one embodiment ofthe present invention.

FIG. 21 is a block diagram illustrating aspects of an example ofmicro-thread concurrency, according to one embodiment of the presentinvention.

DETAILED DESCRIPTION OF THE INVENTION

In the following description, for the purposes of explanation, numerousspecific details are set forth in order to provide a thoroughunderstanding of various embodiments of the present invention. It willbe apparent, however, to one skilled in the art that embodiments of thepresent invention may be practiced without some of these specificdetails. In other instances, well-known structures and devices are shownin block diagram form.

The ensuing description provides exemplary embodiments only, and is notintended to limit the scope, applicability, or configuration of thedisclosure. Rather, the ensuing description of the exemplary embodimentswill provide those skilled in the art with an enabling description forimplementing an exemplary embodiment. It should be understood thatvarious changes may be made in the function and arrangement of elementswithout departing from the spirit and scope of the invention as setforth in the appended claims.

Specific details are given in the following description to provide athorough understanding of the embodiments. However, it will beunderstood by one of ordinary skill in the art that the embodiments maybe practiced without these specific details. For example, circuits,systems, networks, processes, and other components may be shown ascomponents in block diagram form in order not to obscure the embodimentsin unnecessary detail. In other instances, well-known circuits,processes, algorithms, structures, and techniques may be shown withoutunnecessary detail in order to avoid obscuring the embodiments.

Also, it is noted that individual embodiments may be described as aprocess which is depicted as a flowchart, a flow diagram, a data flowdiagram, a structure diagram, or a block diagram. Although a flowchartmay describe the operations as a sequential process, many of theoperations can be performed in parallel or concurrently. In addition,the order of the operations may be re-arranged. A process is terminatedwhen its operations are completed, but could have additional steps notincluded in a figure. A process may correspond to a method, a function,a procedure, a subroutine, a subprogram, etc. When a process correspondsto a function, its termination can correspond to a return of thefunction to the calling function or the main function.

The term “machine-readable medium” includes, but is not limited toportable or fixed storage devices, optical storage devices, wirelesschannels and various other mediums capable of storing, containing orcarrying instruction(s) and/or data. A code segment ormachine-executable instructions may represent a procedure, a function, asubprogram, a program, a routine, a subroutine, a module, a softwarepackage, a class, or any combination of instructions, data structures,or program statements. A code segment may be coupled to another codesegment or a hardware circuit by passing and/or receiving information,data, arguments, parameters, or memory contents. Information, arguments,parameters, data, etc. may be passed, forwarded, or transmitted via anysuitable means including memory sharing, message passing, token passing,network transmission, etc. Various other terms used herein are nowdefined for the sake of clarity.

Virtual memory is a memory management technique that gives the illusionto each software process that memory is as large as the virtual addressspace. The operating system in conjunction with differing degrees ofhardware manages the physical memory as a cache of the virtual addressspace, which is placed in secondary storage and accessible throughInput/Output instructions. Virtual memory is separate from, but caninteract with, a file system.

A single level store is an extension of virtual memory in which thereare no files, only persistent objects or segments which are mapped intoa processes' address space using virtual memory techniques. The entirestorage of the computing system is thought of as a segment and addresswithin a segment. Thus at least three separate address spaces, i.e.,physical memory address/node, virtual address/process, and secondarystorage address/disk, are managed by software.

Object storage refers to the way units of storage called objects areorganized. Every object consists of a container that holds three things:actual data; expandable metadata; and a globally unique identifierreferred to herein as the object address. The metadata of the object isused to define contextual information about the data and how it shouldbe used and managed including relationship to other objects.

The object address space is managed by software over storage devices,nodes, and network to find an object without knowing its physicallocation. Object storage is separate from virtual memory and singlelevel store, but can certainly inter-operate through software.

Block storage consists of evenly sized blocks of data with an addressbased on a physical location and without metadata.

A network address is a physical address of a node within an IP networkthat is associated with a physical location.

A node or processing node is a physical unit of computing delineated bya shared physical memory that be addressed by any processor within thenode.

Object memory is an object store directly accessible as memory byprocessor memory reference instructions and without implicit or explicitsoftware or Input/Output instructions required. Object capabilities aredirectly provided within the object memory to processing through memoryreference instructions.

An object memory fabric connects object memory modules and nodes into asingle object memory where any object is local to any object memorymodule by direct management, in hardware, of object data, meta-data andobject address.

An object router routes objects or portions of objects in an objectmemory fabric based on an object address. This is distinct from aconventional router which forwards data packets to appropriate part of anetwork based on a network address.

Embodiments may be implemented by hardware, software, firmware,middleware, microcode, hardware description languages, or anycombination thereof. When implemented in software, firmware, middlewareor microcode, the program code or code segments to perform the necessarytasks may be stored in a machine readable medium. A processor(s) mayperform the necessary tasks.

Embodiments of the invention provide systems and methods for managingprocessing, memory, storage, network, and cloud computing tosignificantly improve the efficiency and performance of processingnodes. Embodiments described herein can be implemented in a set ofhardware components that, in essence, change the way in whichprocessing, memory, and storage, network, and cloud computing aremanaged by breaking down the artificial distinctions between processing,memory, storage and networking in today's commodity solutions tosignificantly improve the efficiency and performance of commodityhardware. For example, the hardware elements can include a standardformat memory module, such as a (DIMM) and a set of one or more objectrouters. The memory module can be added to commodity or “off-the-shelf”hardware such a server node and acts as a big data accelerator withinthat node. Object routers can be used to interconnect two or moreservers or other nodes adapted with the memory modules and help tomanage processing, memory, and storage across these different servers.Nodes can be physically close or far apart. Together, these hardwarecomponents can be used with commodity servers or other types ofcomputing nodes in any combination to implement the embodimentsdescribed herein.

According to one embodiment, such hardware components can implement anobject-based memory which manages the objects within the memory and atthe memory layer rather than in the application layer. That is, theobjects and associated properties are implemented and managed nativelyin memory enabling the object memory system to provide increasedfunctionality without any software and increasing performance bydynamically managing object characteristics including, but not limitedto persistence, location and processing. Object properties can alsopropagate up to higher application levels.

Such hardware components can also eliminate the distinction betweenmemory (temporary) and storage (persistent) by implementing and managingboth within the objects. These components can eliminate the distinctionbetween local and remote memory by transparently managing the locationof objects (or portions of objects) so all objects appear simultaneouslylocal to all nodes. These components can also eliminate the distinctionbetween processing and memory through methods of the objects to placethe processing within the memory itself

According to one embodiment, such hardware components can eliminatetypical size constraints on memory space of the commodity serversimposed by address sizes. Rather, physical addressing can be managedwithin the memory objects themselves and the objects can in turn beaccessed and managed through the object name space.

Embodiment described herein can provide transparent and dynamicperformance acceleration, especially with big data or other memoryintensive applications by reducing or eliminating overhead typicallyassociated with memory management, storage management, networking anddata directories. Rather, management of the memory objects at the memorylevel can significantly shorten the pathways between storage and memoryand between memory and processing, thereby eliminating the associatedoverhead between each. Various additional details of embodiments of thepresent invention will be described below with reference to the figures.

FIG. 2 is a block diagram illustrating components of an exemplarydistributed system in which various embodiments of the present inventionmay be implemented. In the illustrated embodiment, distributed system200 includes one or more client computing devices 202, 204, 206, and208, which are configured to execute and operate a client applicationsuch as a web browser, proprietary client, or the like over one or morenetwork(s) 210. Server 212 may be communicatively coupled with remoteclient computing devices 202, 204, 206, and 208 via network 210.

In various embodiments, server 212 may be adapted to run one or moreservices or software applications provided by one or more of thecomponents of the system. In some embodiments, these services may beoffered as web-based or cloud services or under a Software as a Service(SaaS) model to the users of client computing devices 202, 204, 206,and/or 208. Users operating client computing devices 202, 204, 206,and/or 208 may in turn utilize one or more client applications tointeract with server 212 to utilize the services provided by thesecomponents. For the sake of clarity, it should be noted that server 212and database 214, 216 can correspond to server 105 described above withreference to FIG. 1. Network 210 can be part of or an extension tophysical network 115. It should also be understood that there can be anynumber of client computing devices 202, 204, 206, 208 and servers 212,each with one or more databases 214, 216.

In the configuration depicted in the figure, the software components218, 220 and 222 of system 200 are shown as being implemented on server212. In other embodiments, one or more of the components of system 200and/or the services provided by these components may also be implementedby one or more of the client computing devices 202, 204, 206, and/or208. Users operating the client computing devices may then utilize oneor more client applications to use the services provided by thesecomponents. These components may be implemented in hardware, firmware,software, or combinations thereof. It should be appreciated that variousdifferent system configurations are possible, which may be differentfrom distributed system 200. The embodiment shown in the figure is thusone example of a distributed system for implementing an embodimentsystem and is not intended to be limiting.

Client computing devices 202, 204, 206, and/or 208 may be portablehandheld devices (e.g., an iPhone®, cellular telephone, an iPad®,computing tablet, a personal digital assistant (PDA)) or wearabledevices (e.g., a Google Glass® head mounted display), running softwaresuch as Microsoft Windows Mobile®, and/or a variety of mobile operatingsystems such as iOS, Windows Phone, Android, BlackBerry 10, Palm OS, andthe like, and being Internet, e-mail, short message service (SMS),Blackberry®, or other communication protocol enabled. The clientcomputing devices can be general purpose personal computers including,by way of example, personal computers and/or laptop computers runningvarious versions of Microsoft Windows®, Apple Macintosh®, and/or Linuxoperating systems. The client computing devices can be workstationcomputers running any of a variety of commercially-available UNIX® orUNIX-like operating systems, including without limitation the variety ofGNU/Linux operating systems, such as for example, Google Chrome OS.Alternatively, or in addition, client computing devices 202, 204, 206,and 208 may be any other electronic device, such as a thin-clientcomputer, an Internet-enabled gaming system (e.g., a Microsoft Xboxgaming console with or without a Kinect® gesture input device), and/or apersonal messaging device, capable of communicating over network(s) 210.

Although exemplary distributed system 200 is shown with four clientcomputing devices, any number of client computing devices may besupported. Other devices, such as devices with sensors, etc., mayinteract with server 212.

Network(s) 210 in distributed system 200 may be any type of networkfamiliar to those skilled in the art that can support datacommunications using any of a variety of commercially-availableprotocols, including without limitation TCP/IP (Transmission ControlProtocol/Internet Protocol), SNA (Systems Network Architecture), IPX(Internet Packet Exchange), AppleTalk, and the like. Merely by way ofexample, network(s) 210 can be a Local Area Network (LAN), such as onebased on Ethernet, Token-Ring and/or the like. Network(s) 210 can be awide-area network and the Internet. It can include a virtual network,including without limitation a Virtual Private Network (VPN), anintranet, an extranet, a Public Switched Telephone Network (PSTN), aninfra-red network, a wireless network (e.g., a network operating underany of the Institute of Electrical and Electronics (IEEE) 802.11 suiteof protocols, Bluetooth®, and/or any other wireless protocol); and/orany combination of these and/or other networks. Elements of suchnetworks can have an arbitrary distance, i.e., can be remote orco-located. Software Defined Networks (SDNs) can be implemented with acombination of dumb routers and software running on servers.

Server 212 may be composed of one or more general purpose computers,specialized server computers (including, by way of example, PersonalComputer (PC) servers, UNIX® servers, mid-range servers, mainframecomputers, rack-mounted servers, etc.), server farms, server clusters,or any other appropriate arrangement and/or combination. In variousembodiments, server 212 may be adapted to run one or more services orsoftware applications described in the foregoing disclosure. Forexample, server 212 may correspond to a server for performing processingdescribed above according to an embodiment of the present disclosure.

Server 212 may run an operating system including any of those discussedabove, as well as any commercially available server operating system.Server 212 may also run any of a variety of additional serverapplications and/or mid-tier applications, including HyperText TransportProtocol (HTTP) servers, File Transfer Protocol (FTP) servers, CommonGateway Interface (CGI) servers, JAVA® servers, database servers, andthe like. Exemplary database servers include without limitation thosecommercially available from Oracle, Microsoft, Sybase, InternationalBusiness Machines (IBM), and the like.

In some implementations, server 212 may include one or more applicationsto analyze and consolidate data feeds and/or event updates received fromusers of client computing devices 202, 204, 206, and 208. As an example,data feeds and/or event updates may include, but are not limited to,Twitter® feeds, Facebook® updates or real-time updates received from oneor more third party information sources and continuous data streams,which may include real-time events related to sensor data applications,financial tickers, network performance measuring tools (e.g., networkmonitoring and traffic management applications), clickstream analysistools, automobile traffic monitoring, and the like. Server 212 may alsoinclude one or more applications to display the data feeds and/orreal-time events via one or more display devices of client computingdevices 202, 204, 206, and 208.

Distributed system 200 may also include one or more databases 214 and216. Databases 214 and 216 may reside in a variety of locations. By wayof example, one or more of databases 214 and 216 may reside on anon-transitory storage medium local to (and/or resident in) server 212.Alternatively, databases 214 and 216 may be remote from server 212 andin communication with server 212 via a network-based or dedicatedconnection. In one set of embodiments, databases 214 and 216 may residein a Storage-Area Network (SAN). Similarly, any necessary files forperforming the functions attributed to server 212 may be stored locallyon server 212 and/or remotely, as appropriate. In one set ofembodiments, databases 214 and 216 may include relational databases thatare adapted to store, update, and retrieve data in response to commands,e.g., MySQL-formatted commands. Additionally or alternatively, server212 can provide and support big data processing on unstructured dataincluding but not limited to Hadoop processing, NoSQL databases, graphdatabases etc. In yet other implementations, server 212 may performnon-database types of bog data applications including but not limited tomachine learning.

FIG. 3 is a block diagram illustrating an exemplary computer system inwhich embodiments of the present invention may be implemented. Thesystem 300 may be used to implement any of the computer systemsdescribed above. As shown in the figure, computer system 300 includes aprocessing unit 304 that communicates with a number of peripheralsubsystems via a bus subsystem 302. These peripheral subsystems mayinclude a processing acceleration unit 306, an I/O subsystem 308, astorage subsystem 318 and a communications subsystem 324. Storagesubsystem 318 includes tangible computer-readable storage media 322 anda system memory 310.

Bus subsystem 302 provides a mechanism for letting the variouscomponents and subsystems of computer system 300 communicate with eachother as intended. Although bus subsystem 302 is shown schematically asa single bus, alternative embodiments of the bus subsystem may utilizemultiple buses. Bus subsystem 302 may be any of several types of busstructures including a memory bus or memory controller, a peripheralbus, and a local bus using any of a variety of bus architectures. Forexample, such architectures may include an Industry StandardArchitecture (ISA) bus, Micro Channel Architecture (MCA) bus, EnhancedISA (EISA) bus, Video Electronics Standards Association (VESA) localbus, Peripheral Component Interconnect (PCI) bus, which can beimplemented as a Mezzanine bus manufactured to the IEEE P1386.1standard, or PCI enhanced (PCIe) bus.

Processing unit 304, which can be implemented as one or more integratedcircuits (e.g., a conventional microprocessor or microcontroller),controls the operation of computer system 300. One or more processorsmay be included in processing unit 304. These processors may includesingle core or multicore processors. In certain embodiments, processingunit 304 may be implemented as one or more independent processing units332 and/or 334 with single or multicore processors included in eachprocessing unit. In other embodiments, processing unit 304 may also beimplemented as a quad-core processing unit formed by integrating twodual-core processors into a single chip.

In various embodiments, processing unit 304 can execute a variety ofprograms in response to program code and can maintain multipleconcurrently executing programs or processes. At any given time, some orall of the program code to be executed can be resident in processor(s)304 and/or in storage subsystem 318. Through suitable programming,processor(s) 304 can provide various functionalities described above.Computer system 300 may additionally include a processing accelerationunit 306, which can include a Digital Signal Processor (DSP), aspecial-purpose processor, and/or the like.

I/O subsystem 308 may include user interface input devices and userinterface output devices. User interface input devices may include akeyboard, pointing devices such as a mouse or trackball, a touchpad ortouch screen incorporated into a display, a scroll wheel, a click wheel,a dial, a button, a switch, a keypad, audio input devices with voicecommand recognition systems, microphones, and other types of inputdevices. User interface input devices may include, for example, motionsensing and/or gesture recognition devices such as the Microsoft Kinect®motion sensor that enables users to control and interact with an inputdevice, such as the Microsoft Xbox® 360 game controller, through anatural user interface using gestures and spoken commands. Userinterface input devices may also include eye gesture recognition devicessuch as the Google Glass® blink detector that detects eye activity(e.g., ‘blinking’ while taking pictures and/or making a menu selection)from users and transforms the eye gestures as input into an input device(e.g., Google Glass®). Additionally, user interface input devices mayinclude voice recognition sensing devices that enable users to interactwith voice recognition systems (e.g., Siri® navigator), through voicecommands.

User interface input devices may also include, without limitation, threedimensional (3D) mice, joysticks or pointing sticks, gamepads andgraphic tablets, and audio/visual devices such as speakers, digitalcameras, digital camcorders, portable media players, webcams, imagescanners, fingerprint scanners, barcode reader 3D scanners, 3D printers,laser rangefinders, and eye gaze tracking devices. Additionally, userinterface input devices may include, for example, medical imaging inputdevices such as computed tomography, magnetic resonance imaging,position emission tomography, medical ultrasonography devices. Userinterface input devices may also include, for example, audio inputdevices such as MIDI keyboards, digital musical instruments and thelike.

User interface output devices may include a display subsystem, indicatorlights, or non-visual displays such as audio output devices, etc. Thedisplay subsystem may be a Cathode Ray Tube (CRT), a flat-panel device,such as that using a Liquid Crystal Display (LCD) or plasma display, aprojection device, a touch screen, and the like. In general, use of theterm “output device” is intended to include all possible types ofdevices and mechanisms for outputting information from computer system300 to a user or other computer. For example, user interface outputdevices may include, without limitation, a variety of display devicesthat visually convey text, graphics and audio/video information such asmonitors, printers, speakers, headphones, automotive navigation systems,plotters, voice output devices, and modems.

Computer system 300 may comprise a storage subsystem 318 that comprisessoftware elements, shown as being currently located within a systemmemory 310. System memory 310 may store program instructions that areloadable and executable on processing unit 304, as well as datagenerated during the execution of these programs.

Depending on the configuration and type of computer system 300, systemmemory 310 may be volatile (such as Random Access Memory (RAM)) and/ornon-volatile (such as Read-Only Memory (ROM), flash memory, etc.) TheRAM typically contains data and/or program modules that are immediatelyaccessible to and/or presently being operated and executed by processingunit 304. In some cases, system memory 310 can comprise one or moreDouble Data Rate fourth generation (DDR4) Dual Inline Memory Modules(DIMMs). In some implementations, system memory 310 may include multipledifferent types of memory, such as Static Random Access Memory (SRAM) orDynamic Random Access Memory (DRAM). In some implementations, a BasicInput/Output System (BIOS), containing the basic routines that help totransfer information between elements within computer system 300, suchas during start-up, may typically be stored in the ROM. By way ofexample, and not limitation, system memory 310 also illustratesapplication programs 312, which may include client applications, Webbrowsers, mid-tier applications, Relational Database Management Systems(RDBMS), etc., program data 314, and an operating system 316. By way ofexample, operating system 316 may include various versions of MicrosoftWindows®, Apple Macintosh®, and/or Linux operating systems, a variety ofcommercially-available UNIX® or UNIX-like operating systems (includingwithout limitation the variety of GNU/Linux operating systems, theGoogle Chrome® OS, and the like) and/or mobile operating systems such asiOS, Windows® Phone, Android® OS, BlackBerry® 10 OS, and Palm® OSoperating systems.

Storage subsystem 318 may also provide a tangible computer-readablestorage medium for storing the basic programming and data constructsthat provide the functionality of some embodiments. Software (programs,code modules, instructions) that when executed by a processor providethe functionality described above may be stored in storage subsystem318. These software modules or instructions may be executed byprocessing unit 304. Storage subsystem 318 may also provide a repositoryfor storing data used in accordance with the present invention.

Storage subsystem 300 may also include a computer-readable storage mediareader 320 that can further be connected to computer-readable storagemedia 322. Together and, optionally, in combination with system memory310, computer-readable storage media 322 may comprehensively representremote, local, fixed, and/or removable storage devices plus storagemedia for temporarily and/or more permanently containing, storing,transmitting, and retrieving computer-readable information.

Computer-readable storage media 322 containing code, or portions ofcode, can also include any appropriate media known or used in the art,including storage media and communication media, such as but not limitedto, volatile and non-volatile, removable and non-removable mediaimplemented in any method or technology for storage and/or transmissionof information. This can include tangible computer-readable storagemedia such as RAM, ROM, Electronically Erasable Programmable ROM(EEPROM), flash memory or other memory technology, CD-ROM, DigitalVersatile Disk (DVD), or other optical storage, magnetic cassettes,magnetic tape, magnetic disk storage or other magnetic storage devices,or other tangible computer readable media. This can also includenontangible computer-readable media, such as data signals, datatransmissions, or any other medium which can be used to transmit thedesired information and which can be accessed by computing system 300.

By way of example, computer-readable storage media 322 may include ahard disk drive that reads from or writes to non-removable, nonvolatilemagnetic media, a magnetic disk drive that reads from or writes to aremovable, nonvolatile magnetic disk, and an optical disk drive thatreads from or writes to a removable, nonvolatile optical disk such as aCD ROM, DVD, and Blu-Ray® disk, or other optical media.Computer-readable storage media 322 may include, but is not limited to,Zip® drives, flash memory cards, Universal Serial Bus (USB) flashdrives, Secure Digital (SD) cards, DVD disks, digital video tape, andthe like. Computer-readable storage media 322 may also include,Solid-State Drives (SSD) based on non-volatile memory such asflash-memory based SSDs, enterprise flash drives, solid state ROM, andthe like, SSDs based on volatile memory such as solid state RAM, dynamicRAM, static RAM, DRAM-based SSDs, Magnetoresistive RAM (MRAM) SSDs, andhybrid SSDs that use a combination of DRAM and flash memory based SSDs.The disk drives and their associated computer-readable media may providenon-volatile storage of computer-readable instructions, data structures,program modules, and other data for computer system 300.

Communications subsystem 324 provides an interface to other computersystems and networks. Communications subsystem 324 serves as aninterface for receiving data from and transmitting data to other systemsfrom computer system 300. For example, communications subsystem 324 mayenable computer system 300 to connect to one or more devices via theInternet. In some embodiments communications subsystem 324 can includeRadio Frequency (RF) transceiver components for accessing wireless voiceand/or data networks (e.g., using cellular telephone technology,advanced data network technology, such as 3G, 4G or Enhanced Data ratesfor Global Evolution (EDGE), WiFi (IEEE 802.11 family standards, orother mobile communication technologies, or any combination thereof),Global Positioning System (GPS) receiver components, and/or othercomponents. In some embodiments communications subsystem 324 can providewired network connectivity (e.g., Ethernet) in addition to or instead ofa wireless interface. In some cases, communications subsystem 324 can beimplemented in whole or in part as one or more PCIe cards.

In some embodiments, communications subsystem 324 may also receive inputcommunication in the form of structured and/or unstructured data feeds326, event streams 328, event updates 330, and the like on behalf of oneor more users who may use computer system 300.

By way of example, communications subsystem 324 may be configured toreceive data feeds 326 in real-time from users of social networks and/orother communication services such as Twitter® feeds, Facebook® updates,web feeds such as Rich Site Summary (RSS) feeds, and/or real-timeupdates from one or more third party information sources.

Additionally, communications subsystem 324 may also be configured toreceive data in the form of continuous data streams, which may includeevent streams 328 of real-time events and/or event updates 330, that maybe continuous or unbounded in nature with no explicit end. Examples ofapplications that generate continuous data may include, for example,sensor data applications, financial tickers, network performancemeasuring tools (e.g. network monitoring and traffic managementapplications), clickstream analysis tools, automobile trafficmonitoring, and the like.

Communications subsystem 324 may also be configured to output thestructured and/or unstructured data feeds 326, event streams 328, eventupdates 330, and the like to one or more databases that may be incommunication with one or more streaming data source computers coupledto computer system 300.

Computer system 300 can be one of various types, including a handheldportable device (e.g., an iPhone® cellular phone, an iPad® computingtablet, a PDA), a wearable device (e.g., a Google Glass® head mounteddisplay), a PC, a workstation, a mainframe, a kiosk, a server rack, orany other data processing system.

Due to the ever-changing nature of computers and networks, thedescription of computer system 300 depicted in the figure is intendedonly as a specific example. Many other configurations having more orfewer components than the system depicted in the figure are possible.For example, customized hardware might also be used and/or particularelements might be implemented in hardware, firmware, software (includingapplets), or a combination. Further, connection to other computingdevices, such as network input/output devices, may be employed. Based onthe disclosure and teachings provided herein, a person of ordinary skillin the art will appreciate other ways and/or methods to implement thevarious embodiments.

As introduced above, embodiments of the invention provide systems andmethods for managing processing, memory, storage, network, and cloudcomputing to significantly improve the efficiency and performance ofprocessing nodes such as any of the servers or other computers orcomputing devices described above. Embodiments described herein can beimplemented in a set of hardware components that, in essence, change theway in which processing, memory, storage, network, and cloud are managedby breaking down the artificial distinctions between processing, memory,storage and networking in today's commodity solutions to significantlyimprove the performance of commodity hardware. For example, the hardwareelements can include a standard format memory module, such as a DualInline Memory Module (DIMM), which can be added to any of the computersystems described above. For example, the memory module can be added tocommodity or “off-the-shelf” hardware such a server node and acts as abig data accelerator within that node. The components can also includeone or more object routers. Object routers can include, for example, aPCI express card added to the server node along with the memory moduleand one or more external object routers such as rack mounted routers,for example. Object routers can be used to interconnect two or moreservers or other nodes adapted with the memory modules and help tomanage processing, memory, and storage across these different serversObject routers can forward objects or portions of objects based onobject addresses and participate in operation of the object memoryfabric. Together, these hardware components can be used with commodityservers or other types of computing nodes in any combination toimplement an object memory fabric architecture.

FIG. 4 is a block diagram illustrating an exemplary object memory fabricarchitecture according to one embodiment of the present invention. Asillustrated here, the architecture 400 comprises an object memory fabric405 supporting any number of applications 410 a-g. As will be describedin greater detail below, this object memory fabric 405 can comprise anynumber of processing nodes such as one or more servers having installedone or more memory modules as described herein. These nodes can beinterconnected by one or more internal and/or external object routers asdescribed herein. While described as comprising one or more servers, itshould be noted that the processing nodes of the object memory fabric405 can comprise any of a variety of different computers and/orcomputing devices adapted to operate within the object memory fabric 405as described herein.

According to one embodiment, the object memory fabric 405 provides anobject-based memory which manages memory objects within the memory ofthe nodes of the object memory fabric 405 and at the memory layer ratherthan in the application layer. That is, the objects and associatedproperties can be implemented and managed natively in the nodes of theobject memory fabric 405 to provide increased functionality without anysoftware and increasing efficiency and performance by dynamicallymanaging object characteristics including, but not limited topersistence, location and processing. Object properties can alsopropagate to the applications 410 a-g. The memory objects of the objectmemory fabric 405 can be used to eliminate typical size constraints onmemory space of the commodity servers or other nodes imposed by addresssizes. Rather, physical addressing can be managed within the memoryobjects themselves and the objects can in turn be accessed and managedthrough the object name space. The memory objects of the object memoryfabric 405 can also be used to eliminate the distinction between memory(temporary) and storage (persistent) by implementing and managing bothwithin the objects. The object memory fabric 405 can also eliminate thedistinction between local and remote memory by transparently managingthe location of objects (or portions of objects) so all objects appearsimultaneously local to all nodes. The memory objects can also eliminatethe distinction between processing and memory through methods of theobjects to place the processing within the memory itself. In otherwords, embodiments of the present invention provide a single-levelmemory that puts the computes with the storage and the storage with thecomputes, directly and thereby eliminating numerous levels of softwareoverhead communicating across these levels and the artificial overheadof moving data to be processed.

In these ways, embodiments of the object memory fabric 405 andcomponents thereof as described herein can provide transparent anddynamic performance acceleration, especially with big data or othermemory intensive applications by reducing or eliminating overheadtypically associated with memory management, storage management,networking, data directories, and data buffers at both the system andapplication software layers. Rather, management of the memory objects atthe memory level can significantly shorten the pathways between storageand memory and between memory and processing, thereby eliminating theassociated overhead between each.

Embodiments provide coherent, hardware-based, infinite memory managed asmemory objects with performance accelerated in-memory, spanning allnodes, and scalable across all nodes. This enables transparent dynamicperformance acceleration based on the object and end application. Usingan architecture according to embodiments of the present invention,applications and system software can be treated the same and as simpleas a single, standard server but additionally allowing memory fabricobjects to capture heuristics. Embodiments provide multiple dimensionsof accelerated performance including locality acceleration. According toone embodiment, object memory fabric metadata associated with the memoryobjects can include triggers which enable the object memory fabricarchitecture to localize and move data to fast dram memory ahead of use.Triggers can be a fundamental generalization that enables the memorysystem to execute arbitrary functions based on memory access. Variousembodiments can also include an instruction set which can provide aunique instruction model for the object memory fabric based on thetriggers defined in the metadata associated with each memory object andthat supports core operations and optimizations and allows the memoryintensive portion of applications to be more efficiently executed in ahighly parallel manner within IMF.

Embodiments can also decrease software path-length by substituting asmall number of memory references for a complex application, storage andnetwork stack. This can be accomplished when memory and storage isdirectly addressable as memory under embodiments of the presentinvention. Embodiments can additionally provide accelerated performanceof high level memory operations. For many cases, embodiments of theobject memory fabric architecture can eliminate the need to move data tothe processor and back to memory, which is extremely inefficient fortoday's modern processors with three or more levels of caches.

FIG. 5 is a block diagram illustrating an exemplary memory fabric objectmemory according to one embodiment of the present invention. Morespecifically, this example illustrates an application view of how memoryfabric object memory can be organized. Memory fabric object addressspace 500 can be a 128 bit linear address space where the object IDcorresponds to the start of the addressable object. Objects 510 can bevariable size from 2¹² to 2⁶⁴ bytes. The address space 500 canefficiently be utilized sparsely within and across objects as objectstorage is allocated on a per block basis. The size of the object space500 is meant to be large enough that garbage collection is not necessaryand to enable disjoint systems to be easily combined.

Object metadata 505 associated with each object 510 can be transparentwith respect to the object address space 500 and can utilize the objectmemory fabric to manage objects and blocks within objects and can beaccessible at appropriate privilege by applications 515 a-g throughApplication Program Interfaces (APIs) of the object memory fabric. ThisAPI provides functions for applications to set up and maintain theobject memory fabric, for example by using modified Linux libc. With asmall amount of additional effort applications such as a SQL database orgraph database can utilize the API to create memory objects and provideand/or augment object metadata to allow the object memory fabric tobetter manage objects. Object metadata 505 can include object methods,which enable performance optimization through dynamic object-basedprocessing, distribution, and parallelization. Metadata can enable eachobject to have a definable security policy and access encapsulationwithin an object.

According to embodiments of the present invention, applications 515 a-gcan now access a single object that captures it's working and/orpersistent data (such as App0 515 a) or multiple objects for finergranularity (such as App1 515 b). Applications can also share objects.Object memory 500 according to these embodiments can physically achievesthis powerfully simple application view with a combination of physicalorganization, which will be described in greater detail below withreference to FIG. 6, and object memory dynamics. Generally speaking, theobject memory 500 can be organized as a distributed hierarchy thatcreates hierarchical neighborhoods for object storage and applications515 a-g. Object memory dynamics interact and leverage the hierarchalorganization to dynamically create locals of objects and applications(object methods) that operate on objects. Since object methods can beassociated with memory objects, as objects migrate and replicate on thememory fabric, object methods naturally gain increased parallelism asobject size warrants. The hierarchy in conjunction with object dynamicscan further create neighborhoods of neighborhoods based on the size anddynamics of the object methods.

FIG. 6 is a block diagram illustrating an exemplary object memorydynamics and physical organization according to one embodiment of thepresent invention. As illustrated in this example, an object memoryfabric 600 as described above can include any number of processing nodes605 and 610 communicatively coupled via one or more external objectrouters 615. Each node 605 and 610 can also include an internal objectrouter 620 and one or more memory modules. Each memory module 625 caninclude a node object memory 635 supporting any number of applications515 a-g. Generally speaking, the memory module 625, node object router620 and inter-node object router 615 can all share a commonfunctionality with respect to the object memory 635 and index thereof.In other words, the underlying design objects can be reused in all threeproviding a common design adaptable to hardware of any of a variety ofdifferent form factors and types in addition to those implementationsdescribed here by way of example.

More specifically, a node can comprise a single node object router 620and one or more memory modules 625 and 630. According to one embodiment,a node 605 can comprise a commodity or “off-the-shelf” server, thememory module 625 can comprise a standard format memory card such as aDual-Inline Memory Module (DIMM) card, and the node object router 620can similarly comprise a standard format card such as a PeripheralComponent Interconnect express (PCIe) card. The node object router 620can implement an object index covering the objects/blocks held withinthe object memory(s) 635 of the memory modules 625 and 630 within thesame node 605. Each memory module 625 and 630 can hold the actualobjects and blocks within objects, corresponding object meta-data, andobject index covering objects currently stored local to that memorymodule. Each memory module 625 and 630 can independently manage bothdram memory (fast and relatively expensive) and flash memory (not asfast, but much less expensive) in a manner that the processor (notshown) of the node 605 thinks that there is the flash amount of fastdram. The memory modules 625 and 630 and the node object router 620 canboth manage free storage through a free storage index implemented in thesame manner as for other indexes. Memory modules 625 and 630 can bedirectly accessed over the standard DDR memory bus by processor cachesand processor memory reference instructions. In this way, the memoryobjects of the memory modules 625 and 630 can be accessed using onlyconventional memory reference instructions and without implicit orexplicit Input/Output (I/O) instructions.

Objects within the object memory 635 of each node 625 can be created andmaintained through an object memory fabric API (not shown). The nodeobject router 620 can communicate with the API through a modified objectmemory fabric version of libc and an object memory fabric driver (notshown). The node object router 620 can then update a local object index,send commands toward a root, i.e., towards the inter-node object router615, as required and communicate with the appropriate memory module 625or 630 to complete the API command locally. The memory module 625 or 630can communicate administrative requests back to the node object router620 which can handle them appropriately.

According to one embodiment, the internal architecture of the nodeobject router 620 can be very similar to the memory module 625 with thedifferences related to routing functionality such as managing a nodememory object index and routing appropriate packets to and from thememory moduels 625 and 630 and the inter-node object router 615. Thatis, the node object router 620 can have additional routing functionalitybut does not need to actually store memory objects.

The inter-node object router 615 can be considered analogous to an IProuter. However, the first difference is the addressing model used. IProuters utilize a fixed static address per each node and routes based onthe destination IP address to a fixed physical node. However, theinter-node object router 615 of the object memory fabric 600 utilizes amemory fabric object address (OA) which specifies the object andspecific block of the object. Objects and blocks can dynamically resideat any node. The inter-node object router 615 can route OA packagesbased on the dynamic location(s) of objects and blocks and trackobject/block location dynamically in real time. The second difference isthat the object router can implement the object memory fabricdistributed protocol which provides the dynamic nature of object/blocklocation and object functions, for example including, but not limited,to triggers. The inter-node object router 615 can be implemented as ascaled up version of node object router 620 with increased object indexstorage capacity, processing rate and overall routing bandwidth. Also,instead of connecting to a single PCIe or other bus or channel toconnect to memory modules, inter-node object router 615 can connect tomultiple node object routers and/or multiple other inter-node objectrouters. According to one embodiment, a node object router 620 cancommunicate with the memory modules 625 and 630 with direct memoryaccess over PCIe and the memory bus (not shown) of the node 605. Nodeobject routers of different nodes 605 and 610 can in turn connect withone or more inter-node object routers 615 over a high-speed network (notshown) such as 25/100GE fiber that uses several layers of GigabitEthernet protocol or object memory fabric protocol tunneled throughstandard IP, for example. Multiple inter-node object routers can connectwith the same network.

In operation, the memory fabric object memory can physically achieve itspowerfully simple application view described above with reference toFIGS. 4 and 5 with a combination of physical organization and objectmemory dynamics. According to one embodiment and as introduced abovewith reference to FIG. 5, the memory fabric object memory can beorganized as a distributed hierarchy that creates hierarchicalneighborhoods for object storage and applications 515 a-g. The nodeobject routers can keep track of which objects and portions of objectsare local to a neighborhood. The actual object memory can be located onnodes 605 or 610 close to applications 515 a-g and memory fabric objectmethods.

Also as introduced above, object memory dynamics can interact andleverage the hierarchal organization to dynamically create locals ofobjects and applications (object methods) that operate on objects. Sinceobject methods can be associated with objects as objects migrate andreplicate across nodes, object methods naturally gain increasedparallelism as object size warrants. This object hierarchy, inconjunction with object dynamics, can in turn create neighborhoods ofneighborhoods based on the size and dynamics of the object methods.

For example, App0 515 a spans multiple memory modules 625 and 630 withina single level object memory fabric neighborhood, in this case node 605.Object movement can stay within that neighborhood and its node objectrouter 620 without requiring any other communication links or routers.The self-organizing nature along the hierarchy defined neighborhoodsprovides efficiency from a performance and minimum bandwidthperspective. In another example, App1 (A1) 515 b can have the samecharacteristic but in a different neighborhood, i.e., in node 610. App2(A2) 515 c can be a parallel application across a two-level hierarchyneighborhood, i.e., nodes 605 and 610. Interactions can beself-contained in the respective neighborhood.

As noted above, certain embodiments may include a data types andmetadata architecture certain embodiments can also include a data typesand metadata architecture that facilitate multiple advantages of thepresent invention. With respect to the architecture, the followingdescription discloses various aspects of: object memory fabric addressspaces; an object memory fabric coherent object address space; an objectmemory fabric distributed object memory and index; an object memoryfabric index; object memory fabric objects; and an extended instructionexecution model. Various embodiments may include any one or combinationof such aspects.

FIG. 7 is a block diagram illustrating an aspect of object memory fabrichierarchy of object memory, which localizes working sets and allows forvirtually unlimited scalability, according to one embodiment of thepresent invention. As disclosed herein, certain embodiments may includecore organization and data types that enable the object memory fabric todynamically operate to provide the object memory application view. Thecore organization and data types facilitate the fractal-likecharacteristics of the system which allow the system to behaveidentically in a scale-independent fashion. In the depicted example, anobject memory fabric 700 as disclosed herein can include any number ofprocessing nodes 705 and 710 communicatively coupled at higher levelsvia one or more external object routers, such as object router 715,which may in turn be coupled to one or more higher level object routers.

Specifically, the system may be a fat-tree built from nodes, from leafnodes to root node(s). According to certain embodiments, each node mayjust understand whether its scope encompasses an object and based onthat whether to route a request/response toward the root or leaf.Putting these nodes together enables a system to dynamically scale toany capacity, without impacting the operation or perspective of anynode. In some embodiments, the leaf node may be a DIMM built fromstandard memory chips, plus object memory fabric 700 implemented withinan FPGA. In some embodiments, standard memory chips could have objectmemory fabric 700 imbedded. In various embodiments, implementations mayhave remote nodes such as mobile phones, drones, cars, internet ofthings components, and/or the like.

To facilitate various advantageous properties of object memory fabric700, certain embodiments may employ coherent object memory fabricaddress spaces. Table 1 below identifies non-limiting examples ofvarious aspects of address spaces, in accordance with certainembodiments of the present disclosure. All nodes that are connected to asingle object memory fabric 700, local or distributed, can be consideredpart of a single system environment according to certain embodiments. Asindicated in Table 1, object memory fabric 700 can provide a coherentobject address space. In some embodiments, a 128-bit object addressspace may be provided. However, other embodiments are possible. Thereare several reasons for a large object address space, including thefollowing. The object address space is to directly uniquely address andmanage all memory, storage across all nodes within an object memoryfabric system, and provide a unique address for conventional storageoutside of an object memory fabric system. The object address space canallow an address to be used once and never garbage collect, which is amajor efficiency. The object address space can allow a distinctionbetween allocating address space and allocating storage. In other words,the object address space can be used sparsely as an effective techniquefor simplicity, performance, and flexibility.

As further indicated in Table 1, the object memory fabric 700 candirectly support per-process virtual address spaces and physical addressspaces. With some embodiments, the per-process virtual address spacesand physical address spaces may be compatible with x86-64 architecture.In certain embodiments, the span of a single virtual address space maybe within a single instance of Linux OS, and may be usually coincidentwith a single node. The object memory fabric 700 may enable the samevirtual address space to span more than a single node. The physicaladdress space may be the actual physical memory addressing (e.g., withinan x86-64 node in some embodiments).

TABLE 1 Address Spaces Object memory fabric Object Physical ParameterAddress Space Virtual Address Address Description Object memory Processaddress Cache of fabric handle to object address object memory memoryfabric fabric address Scope Global Per process, can Per node be sharedSize 2¹²⁸ 2⁶⁴ (2⁴⁸ Haswell) 2⁴⁶ (Haswell) Object Yes, object memory Yes,page tables Yes, object Support fabric object index memory tree and perobject fabric index tree metadata Object Sizes 2^({12) ^(|) ^(21 |)^(30 |) ^(39 |48 |) ^(57 |) ^(64}) Address Space Sparse-with orSparse-with or Sparse-page Allocation without storage, without storage,object units object units Storage Object or Based on object PageAllocation block (page) memory fabric Security Through virtual Operatingsystem Operating (Access) address, operating system/ system, and objectmemory file system fabric

FIG. 8 is a block diagram illustrating an example relationship 800between object address space 805, virtual addresses 810, and physicaladdresses 815, in accordance with certain embodiments of the presentdisclosure. With object address space 805, a single object can range insize. By way of example without limitation, a single object can range insize from 2 megabytes (2²¹) to 16 petabytes (2⁶⁴). Other ranges arepossible. Within the object memory fabric 700, object address space 805may be allocated on an object granularity basis in some embodiments. Insome embodiments, storage may be allocated on a 4k byte block basis(e.g., blocks 806, 807). Thus, the object address space block 806, 807in some embodiments may correspond to the 4k byte page size withinx86-64 architecture. When the object address space 805 is created, onlythe address space and object metadata may exist. When storage isallocated on a per block basis, there can be data stored in thecorresponding block of the object. Block storage can be allocated in asparse or non-sparse manner and pre and/or demand allocated. Forexample, in some embodiments, software can use an object as a hashfunction and only allocate physical storage for the valid hashes.

Referring to the example of FIG. 8, within a node 820, 825, which couldbe a conventional server in some embodiments, physical pagescorresponding to physical addresses 815 may be allocated on a dynamicbasis corresponding to the virtual addresses 810. Since object memoryfabric 700 actually provides the physical memory within a node 820, 825by way of the object memory fabric DIMM, when a virtual address segment811, 812, 813, 814 is allocated, an object address space 805 objectwhich corresponds to the particular segment 811, 812, 813, 814 can alsobe created. This enables the same or a different virtual address 810across nodes 820, 825 to address and access the same object. The actualphysical address 815 at which a block/page within an object resideswithin a node 820, 825 can vary over time within or across nodes 820,825, transparently to application software.

Certain embodiments of the object memory fabric 700 may provide keyadvantages: embodiments of object memory fabric 700 may provideintegrated addressing, objects with transparent invariant pointers (noswizzling required), and methods to access a large address space acrossnodes—a with certain embodiments being compatible with x84-64, Linux,and applications. Normally, systems have numerous different addresses(e.g., for memory address with separate address space, sectors,cylinders, physical disks, database systems, file systems, etc.), whichrequires significant software overhead for converting, buffering, andmoving objects and blocks between different layers of addresses. Usingintegrated addressing to address objects, and blocks within objects, andusing the object namespace eliminates layers of software by havingsingle-level addressing invariant across all nodes/systems. With asufficiently large address space, one address system is not invariantwith particular database application and all these systems workingtogether.

Thus, a node may include a memory module may store and manage one ormore memory objects, where physical address of memory and storage ismanaged with each of the one or more memory objects based at least inpart on an object address space that is allocated on a per-object basiswith a single-level object addressing scheme. The node may be configuredto utilize the object addressing scheme to operatively couple to one ormore additional nodes to operate as a set of nodes of an object memoryfabric, where the set of nodes operates so that all memory objects ofthe set of nodes are accessible based at least in part on the objectaddressing scheme, the object addressing scheme defining invariantobject addresses for the one or more memory objects that are invariantwith respect to physical memory storage locations and storage locationchanges of the one or more memory objects within the memory module andacross all modules interfacing the object memory fabric. Accordingly,the object addresses are invariant within a module and across allmodules that interface to object memory fabric, regardless of whetherthe objects are in a single server or not. Even though the objects canbe stored on any or all modules, the object addresses are stillinvariant no matter at which physical memory locations the objects arecurrently or will be stored. The following provides details of certainembodiments that may provide such advantages through the object addressspace and object address space pointers.

Certain embodiments of object memory fabric 700 may support multiple,various pointer formats. FIG. 9 is a block diagram illustrating anexample relationship 900 between object sizes 905 and object addressspace pointers 910, in accordance with certain embodiments of thepresent disclosure. Table 2 below identifies non-limiting examples ofaspects of the object address space pointer 910, in accordance withcertain embodiments of the present disclosure. As indicated by Table 2,some example embodiments can support three pointer formats. The objectaddress space format may be a object memory fabric native 128 bit formatand can provide a single pointer with full addressability for any objectand offset within object. Object memory fabric 700 can supportadditional formats, for example, two additional formats in 64 bit formatto enable direct compatibility with x86-64 virtual memory and virtualaddress. Once a relationship between an object memory fabric object anda virtual address segment is established by object memory fabric API(which can be handled transparently to the application in Linux libc, insome embodiments), standard x86 Linux programs can directly referencedata within an object (x86 segment) efficiently and transparentlyutilizing the x86-64 addressing mechanisms.

TABLE 2 Object Address Space Pointer Formats Object Object memoryAddress Transformation Virtual Pointer fabric Space to Virtual AddressType Pointer Generation Address Format Object 128 bit Direct None Nonememory Storage fabric Address Object Offset Obj Start + None virtualaddress Relative (64 bit) Obj Offset base + offset address mode ObjectOffset Obj Start + Add virtual 48 bit virtual Virtual (64 bit) ObjOffset address base address with 64 Address to offset bit data type

Table 3 below identifies non-limiting examples of aspects of the objectaddress space pointers in relation to object sizes, in accordance withcertain embodiments of the present disclosure. Embodiments of objectaddress space can supports multiple segment sizes, for example, sixsegment sizes from 2²¹ to 2⁶⁴ as illustrated in Table 3 below. Theobject sizes correspond to the x86-64 virtual memory segment and largepage sizes. Objects can start on a modulo 0 object size boundary. Objectaddress space pointers 910 may be broken into Obj Start and Obj Offsetfields, the sizes of which are dependent on the object size as shown inthe example below. The Obj Start field corresponds to the object addressspace start of the object and also the ObjectID. The Obj Offset is anunsigned value in a range from zero to (ObjectSize-1) with specifies theoffset within an object. Object metadata can specify the object size andobject memory fabric interpretation of the object address space pointer910. Objects of arbitrary size and sparseness can be specified by onlyallocating storage for blocks of interest within an object.

Because of the nature of most applications and object nature of objectmemory fabric 700, most addressing can be relative to an object. In someembodiments, all the object memory fabric address pointer formats can benatively stored and loaded by the processor. Object Relative and ObjectVirtual Address can work directly with x86-64 addressing modes in someembodiments. Object Virtual Address pointer can be or include a processvirtual address that works within the x86-64 segment and correspondingobject memory fabric object. Object memory fabric object address spacecan be calculated by using the Object Virtual Address as an objectoffset. Object Relative pointer can be or include an offset into anx86-64 virtual address segment, thus base plus index addressing modeworks perfectly. Object memory fabric object address space can becalculated by using the Object Relative as an object offset. Table 3below identifies non-limiting examples of details of generating a 128bit object address space from an Object Virtual Address or ObjectRelative pointer as a function of object size, in accordance withcertain embodiments of the present disclosure.

TABLE 3 Object Address Space Generation Object Address Space Generationfrom Object Object Relative and Object Virtual Size Address Pointers 2²¹IA[127:00] = (ObjBase[127:21], zero[20:0]) + (zero[127:21],ObjOffset[20.0]) 2³⁰ IA[127:00] = (ObjBase[127:30], zero[29:0]) +(zero[127:30], ObjOffset[29.0]) 2³⁹ IA[127:00] = (ObjBase[127:39],zero[38:0]) + (zero[127:39], ObjOffset[38.0]) 2⁴⁸ IA[127:00] =(ObjBase[127:48], zero[47:0]) + (zero[127:48], ObjOffset[47.0]) 2⁵⁷IA[127:00] = (ObjBase[127:57], zero[56:0]) + (zero[127:57],ObjOffset[56.0]) 2⁶⁴ IA[127:00] = (ObjBase[127:21], zero[20:0]) +(zero[127:21], ObjOffset[20.0])

As disclosed herein, certain embodiments may include an object memoryfabric distributed object memory and index. With the distributed index,individual nodes may index local objects and blocks of objects on aper-object basis. Certain embodiments of object memory fabricdistributed object memory and index may be based at least in part on anintersection concept of cellular automata and fat trees. Priordistributed hardware and software systems with real-time dynamic indicesused two approaches: a centralized index or a distributed singleconceptual index. Embodiments of object memory fabric may use a newapproach which overlays an independent local index function on top of afat-tree hierarchical network.

FIG. 10 is a block diagram illustrating an example object memory fabricdistributed object memory and index structure 1000, in accordance withcertain embodiments of the present disclosure. At leaves of thestructure 1000 are any number of processing nodes 1005 and 1010 objectmemories 1035. These object memories 1035 may each have an object indexthat describes the objects and portions of objects currently storedlocally in the object memories 1035. A number of object memories 1035,which in some embodiments may be DDR4-DIMM interface compatible cardswithin a single node are logically connected with an object memoryfabric node object index 1040. The object memory fabric node objectindices 1040 may each have an object index that describes the objectsand portions of objects currently stored locally and/or currently storedin the object memories 1035. In some embodiments, the object memoryfabric node object index 1040 can be instantiated as a PCIe card. Withsome embodiments, the object memory fabric object memory DDR4-DIMM andobject memory fabric node object index PCIe card can communicate overPCIe and memory bus.

In some embodiments, the object memory fabric node object index 1040works identically to the object index within the object memory 1035,except that the object memory fabric node object index 1040 tracks allobjects and portions of objects that are within any of the connectedobject memories 1035 and maps the objects and portions of objects toparticular object memory 1035. The next level up in the tree is an nodeobject router object index 1020 that may be provided by an object memoryfabric router that performs the same object index function for all theobject memory fabric node object indices 1040 to which it is connected.The node object router object indices 1020 may each have an object indexthat describes the objects and portions of objects currently storedlocally in lower levels (e.g., at 1040, 1035). Thus, according to someembodiments, router modules may have directory and router functions,whereas memory modules may have directory and router functions, as wellas memory functions to store memory objects. However, other embodimentsare possible, and, in alternative embodiments, the router modules mayadditionally have memory functions to store memory objects.

The pattern may illustrated by the structure 1000 may continue toanother higher level inter-node object router object index 1015 that maybe provided by an object memory fabric router that performs the sameobject index function for all the object memory fabric node objectindices to which it is connected, and so on to the root of the tree.Thus, in certain embodiments, each object index and each level mayperform the same function, independently, but, the aggregate of objectindices and levels as a tree network may provide a real time dynamicdistributed index, with great scalability properties, that efficientlytracks and localizes memory objects and blocks. An additional propertymay be that the combination of tree, distributed indices, and cachingenable a significant reduction in bandwidth requirements. This may beillustrated by the hierarchically indicated neighborhoods that aredelineated by object memory fabric router to leafs (down in this case).As the level of the defined hierarchy increases, so does the aggregateobject memory caching capacity. So, as an application working set fitswithin the aggregate capacity of a given level, the bandwidthrequirement at the level toward the root may go to zero.

As disclosed herein, each processing node is configured to utilize a setof algorithms to operatively couple to one or more additional processingnodes to operate as a set of processing nodes independently of a scaleof the set of processing nodes. The set of nodes may operate so that allmemory objects of the set of nodes are accessible by any node of theprocessing set of nodes. At the processing nodes, object memory modulesmay store and manage memory objects, each instantiated natively thereinand managed at a memory layer, and object directories that index thememory objects and blocks thereof on a per-object basis. A memory modulemay process requests based at least in part on the one or more objectdirectories, which requests may be received from an application layer.In some case, the requests may be received from one or more additionalprocessing nodes. Responsive to the requests, a given memory module mayprocess an object identifier corresponding to a given request and maydetermine whether the memory module has requested object data. If thememory module has the requested object data, the memory module maygenerate a response to the request based at least in part on therequested object data. If the memory module does not have the requestedobject data, an object routing module may routes the first request toanother node in the tree. The routing of the request may be based atleast in part on the object routing module making a determination abouta location of object data responsive to the request. If the objectrouting module identifies the location based at least in part on theobject routing module's directory function, the object routing modulemay rout the request down toward the location (i.e., a lower level nodepossessing the requested object data). However, if the object routingmodule determines that the location is unknown, the object routingmodule may rout the request toward a root node (i.e., to one or morehigher level object routers-inter-node object routers) for furtherdeterminations at each level until the requested object is located,accessed, and returned to the original memory module.

In addition, as disclosed herein, triggers may be defined for objectsand/or blocks within objects in object metadata. The object-basedtriggers may predict what operations will be needed and may provideacceleration by performing the operations ahead of time. When a nodereceives a request that specifies an object (e.g., with a 128-bit objectaddress), the node uses an object directory to determine if the node hasany part of the object. If so, the object directory points to aper-object tree (a separate one, where the size is based on the size ofthe object) which may be used to locate local the blocks of interest.There could be additional trigger metadata that indicates, for theparticular blocks of interest, to interpret the particular addresses ina predefined manner as the blocks are transferred to/through the memorymodule. The triggers may specify one or more pre-defined hardware and/orsoftware actions on a per-block basis with respect to one or more datablocks within an object (e.g., fetch a particular address, run a morecomplicated trigger program, perform pre-fetching, calculate these otherthree blocks and send signal to software, etc.). Triggers may correspondto a hardware way to dynamically move data and/or perform other actionsahead of when such actions are needed as objects flow through any memorymodule of the object memory fabric. Accordingly, such actions may beeffected when a particular memory object having one or more trigger islocated at a respective memory module and accessed as part of therespective memory module processing one or more other requests.

FIGS. 11 and 12 are block diagrams illustrating examples at a logicallevel of how the distributed nature of the object index operates andinteroperates with the object memory fabric protocol layering, inaccordance with certain embodiments of the present disclosure. Certainembodiments of object memory fabric protocol layering may be similar to,but have important differences from, a conventional layeredcommunication protocol. A communications protocol may be essentiallystateless, but embodiments of the object memory fabric protocol maymaintain object state and directly enable distributed and parallelexecution—all without any centralized coordination.

FIG. 11 illustrates an object memory hit case 1100 that executescompletely within the object memory 1135, in accordance with certainembodiments of the present disclosure. Object memory 1135 may receive aprocessor request 1105 or background trigger activity 1106. The objectmemory 1135 may manage the local DRAM memory as a cache 1130, based onprocessor physical address. The most frequent case may be that therequested physical address is present and it gets immediately returnedto the processor, as indicated at 1110. The object memory 1135 may usetriggers to transparently move data from slower flash memory into thefast DRAM memory, as indicated at 1115.

For the case of a miss 1115 or background trigger activity 1106, someembodiments may include one or a combination of the following. In someembodiments, an object memory fabric object address may be generatedfrom the physical address, as indicated by block 1140. The object indexmay generate the location in local flash memory from the object addressspace, as indicated by block 1145. Object index lookup can beaccelerated by two methods: (1) a hardware-based assist for indexlookup; and (2) results of the object index lookup being locally cached.Object memory fabric cache coherency may be used to determine whetherthe local state is sufficient of the intended operation, as indicated byblock 1150. Based on the index, a lookup may be performed to determinewhether the object and/or block within object are local, as indicated byblock 1155. In the case of a hit 1160, the data corresponding to request1105 or trigger activity 1106 may be transferred, as indicated by 1165.And, in some embodiments, when the cache state is sufficient, a decisionmay be made to cache the block into DRAM.

FIG. 12 illustrates an object memory miss case 1200 and the distributednature of the object memory and object index, in accordance with certainembodiments of the present disclosure. The object memory 1235 may gothrough steps described previously, but the routing/decision stage 125may determine that the object and/or block is not local. As a result,the algorithm may involve the request traversing 1270 up the tree towardthe root, until the object/block is found. Any number of levels andcorresponding node elements may be traversed until the object/block isfound. In some embodiments, at each step along the path, the same orsimilar process steps may be followed to independently determine thenext step on the path. No central coordination is required.Additionally, as disclosed herein, object memory fabric API and triggersnormally get executed in the leafs, but can be executed in a distributedmanner at any index.

As a simplified example, in the case depicted the request traverses 1270up from the object memory fabric node object index 1240 corresponding toobject memory 1235 to the object router 1220. The object router 1220,with its an object router object index, may identify the requestobject/block as being down the branch toward object memory fabric nodeobject index 1241. Hence, at the index of object router 1220, therequest may then be routed 1275 toward the leaf(s) that can supply theobject/block. In the example depicted, the object memory 1236 can supplythe object/block. At the object memory 1236, memory access/caching 1241may be performed (which may include previously described process stepsfor a hit case being performed), and the object/block may be returned1280 back to the original requesting leaf 1235 for the ultimate return1290. Again, in some embodiments, at each step along the path, the sameor similar process steps may be followed to independently determine thenext step on the path. For example, the original requesting leaf 1235may perform previously described process steps 1285 for a hit case, andthen return 1290 the requested data.

As disclosed herein, the operation of a single object memory fabricindex structure, the object memory fabric index structure may be basedon several layers of the same tree implementation. Certain embodimentsemploying tree structure may have several uses within object memoryfabric as described in Table 4 below. However, various other embodimentsare possible.

TABLE 4 Tree Structure Uses Node Object Object Object Memory Use MemoryIndex Fabric Router Determine local location of Yes objects and blockscomprising objects as function of object address space Determine whichchildren hold Yes Yes objects, and blocks comprising objects, as afunction of object address space Generate object address space Yes asfunction of local physical address (single level) Object virtual addressto object Yes address space Application defined Yes

FIG. 13 is a block diagram illustrating an example of leaf level objectmemory structure 1300 in view of the object memory fabric distributedobject memory and index structure, in accordance with certainembodiments of the present disclosure. In some embodiments, the leaflevel object memory structure 1300 may include a nested set of B-trees.The root tree may be the object index tree (OIT) 1305, which may indexobjects locally present. The index for the object index tree 1305 may bethe object memory fabric object address, since objects start at objectsize modulo zero. There may be one object index tree 1305 for eachobject that has at least a single block stored locally within the objectmemory.

The object index tree 1305 may provide one or more pointers (e.g., localpointers) to one or more per object index trees (POIT) 1310. Forexample, every local object may have a per object index tree 1310. A perobject index tree 1310 may index object metadata and blocks belonging tothe object that are locally present. The per object index tree 1310leaves point to the corresponding metadata and blocks (e.g., based onoffset within object) in DRAM 1315 and flash 1320. A leaf for a specificblock can point to both DRAM 1315 and flash 1320, as in the case of leaf1325, for example. Organization of object metadata and data is disclosedfurther herein.

The tree structure utilized may be a modified B-tree that iscopy-on-write (COW) friendly. COW is an optimization strategy thatenables multiple tasks to share information efficiently withoutduplicating all storage where most of the data is not modified. COWstores modified blocks in a new location which works well for flashmemory and caching. In certain embodiments, the tree structure utilizedmay be similar to that of the open source Linux file system btrfs, withmajor differences being utilization for a single object/memory space,hardware acceleration, and the ability of independent local indices toaggregate as described previously. By utilizing multiple layers ofB-trees, there can be a higher degree of sharing and less rippling ofchanges. Applications, such as file systems and database storagemanagers, can utilize this underlying efficient mechanism for higherlevel operation.

FIG. 14 is a block diagram illustrating an example of object memoryfabric router object index structure 1400, in accordance with certainembodiments of the present disclosure. With some embodiments, the objectmemory fabric router object index and the node object index may use analmost identical structure of object index trees 1405 and per objectindex trees 1410 for each object. The object index trees 1405 may indexobjects locally present. Each object described in an object index tree1405 may have a per object index tree 1410. The per object index trees1410 may index blocks and segments that are locally present.

The object memory fabric router object index and the node object indexmay index objects and blocks within objects that are present in thechildren 1415 within the tree structure 1400, namely child router(s) orleaf object memory. An entry within a leaf in the per object index tree1410 has the ability to represent multiple blocks within the object.Since blocks of an object may tend to cluster together naturally and dueto background housekeeping, each object tends be represented much morecompactly in object indices that are closer to the tree root. The objectindex trees 1405 and per object index trees 1410 may enablereduplication at the object and block level, since multiple leafs canpoint to the same blocks, as in the case of leaves 1425 and 1430, forexample. Index Copy-On-Write (COW) support enables, for example, onlymodified blocks to be updated for an object.

FIGS. 15A and 15B are block diagrams illustrating non-limiting examplesof index tree structures, including node index tree structure 1500 andleaf index tree 1550, in accordance with certain embodiments of thepresent disclosure. Further non-limiting examples of various aspects ofindex tree fields are identified in Table 5 below. Other embodiments arepossible. An individual index tree may include node blocks and leafblocks. Each node or leaf block may include of a variable number ofentries based on the type and size. Type specifies type of node, nodeblock, leaf, and/or leaf block.

TABLE 5 Index Tree Fields Name Description Size NSize Encoded node sizefield. Single value for OIT 3 node. Multiple values for POIT node basedon object size corresponding to POIT index. Implies the size of NValuefield. ObjSize Encoded Object Size 3 ObjectID Maximum size object ID 107Object Offset 4k block Based on Object size corresponding to 52 POITindex (9-52) LPointer References local 4k block in flash or dram.Includes 32 (LP) 32 bits of pointer and a single bit specifying dramaddress space. LParent Local Parent references the local 4k block of theparent 33 (LPt) node in flash or dram. Includes 32 bits of pointer and asingle bit specifying dram address space. LSize Encoded leaf LValuesize. 3 Otype Type of OIT Leaf 2 Ptype Type of POIT Leaf 2 Etype Type ofOIT or POIT Entry Node 3 Rtype Type of reserved Leaf 3 num May beutilized to increase the size of data that the leaf 0 specifies toincrease the efficiency of index tree and storage device. Values mayinclude: 1 block 4 blocks (flash page) 512 blocks (minimum size object,2 Mbyte) Children Specifies a remote device number 32 Block StateEncoding of 4k block cache coherency state 8 Block referenced count(unsigned) 7 Modified—Indicates that the block has been 1 modified withrespect to persistent store. Only valid for blocks while they arepresent in volatile memory. DS State DownStream State [15:0]—Enumeratesthe state of 128 [15:0] for the block within object specified by ObjectOffset for each of 16 devices.

Size specifies independently the size of the LPointer and IndexVal (orobject offset). Within a balanced tree, a single block may point to allnode blocks or all leaf blocks. In order to deliver highest performance,the tree may become un-balanced, such as for example where the number oflevels for all paths through the tree are equivalent. Node blocks andleaf blocks may provide fields to support un-balanced trees. Abackground activity may re-balance the trees that are part of otherbackground operations. For example, an interior node (non-leaf) in OITmay include L Pointer and NValue fields. NValue may include object sizeand object ID. Object ID requires 107 (128-21) bits to specify thesmallest possible object. Each LPointer may point to the next level ofinterior node or a leaf node. LPointer may require enough bits torepresent all the blocks within its local storage (approximately 32 bitsrepresenting 16 terabytes). For a node in the POIT, the NValue mayconsist of the object offset based on object size. The object size maybe encoded within the NSize field. The size field may enable a node tohold the maximum number of LPointer and NValue fields based on usage. Anindex tree root node may be stored at multiple locations on multipleflash devices to achieve reliable cold boot of the OIT. Tree root blockupdates may be alternated among mirrors to provide wear leveling.

By default, each POIT Leaf entry may point to the location of a singleblock (e.g., 4k bytes). POIT Leaf OM entry and POIT Leaf Router entrymay contain a field to enable support beyond single block to enable morecompressed index trees, higher resulting index tree performance andhigher persistent storage performance by being able to match the pagesize for persistent storage.

Nodes and leafs may be differentiated by the Type field at the start ofeach 4k block. The NNize field may encode the size of NValue fieldwithin a node, and LSize field may encode the size of the LValue fieldwithin a leaf. The size of the LPointer field may be determined by thephysical addressing of local storage is fixed for a single devices(e.g., RDIMM, node router, or router). The LPointer may be only validwithin a single device and not across devices. The LPointer may specifywhether the corresponding block is stored in persistent memory (e.g.,flash) or faster memory (e.g., DRAM). Blocks that are stored in DRAM mayalso have storage allocated within persistent memory, so that twoentries are present to indicate the two storage locations for a block,node or leaf. Within a single block type, all NValue and/or LValuefields may be a single size.

The OIT Node may include several node level fields (Type, NSize, andLParent) and entries including OIT Node Entry or OIT Leaf Entry. Sincean index tree can be un-balanced at times a node can include both nodeand leaf entries. The POIT Node may include one or more node levelfields (e.g., Type, NSize, and/or LParent) and entries including OITLeaf Entry. OIT Leaf types may be differentiated by the otype field. OITLeaf (Object Index Table Leaf) may point to the head of a POIT (PerObject Index Table) that specifies object blocks and object metadata.OIT Leaf R may point to a remote head of an POIT. This may be utilizedto reference an object that is residing on a remote device across anetwork. This leaf may enable the remote device to manage the object.

POIT Leaf types may be differentiated by the ptype field. POIT Leaf OMmay point to a block of object memory or metadata. The Object offsetfield may be one bit greater than the number of bits to specify theoffset for a specific object size to specify metadata. For example, for2²¹ object size 10 bits may be required (9 plus 1 bits). Theimplementation can choose to represent the offset in two's complementform (signed form, first block metadata is −1), or in one's complementwhere the additional bit indicates metadata (first block of metadata isrepresented by 1, with metadata bit set).

POIT Leaf Remote may point to an block of object memory or metadata thatis remote from the local DIMM. This may be used to reference a blockthat is residing on a remote device across a network through the streampackage interface. For example, this device could be a mobile device.This leaf may enable object memory fabric hardware to manage coherenceon a block basis for the remote device.

POIT Leaf Router may be utilized within node object routers andinter-node object routers to specify the state of the correspondingobject memory fabric Block Object Address for each of up to 16downstream nodes. If within a node object router, up to 16 DIMMs may bespecified in some embodiments (or more in other embodiments). If withinan inter-node object router up to 16 downstream routers or node objectrouters (e.g., server nodes) may be specified in some embodiments (ormore in other embodiments). The Block Object Address can be present inone or more downstream devices based on valid state combinations.

Index lookups, index COW updates, and index caching may be directlysupported in object memory fabric hardware in Object Memory, node objectindex, and object memory fabric Router. In addition to the node formatsfor object memory fabric indices, application-defined indices may besupported. These may be initialized through the object memory fabricAPI. An advantage of application-defined indices may be that objectmemory fabric hardware-based index lookup, COW update, index caching,and parallelism may be supported

Various embodiments may provide for background operations and garbagecollection. As each DIMM and Router within object memory fabric maymaintain its own directory and storage locally, background operationsand garbage collection may be accomplished locally and independently.Each DIMM or Router may have a memory hierarchy for storing index treesand data blocks, that may include on-chip cache, fast memory (e.g., DDR4or HMC DRAM) and slower nonvolatile memory (e.g., flash) that it canmanage, as well as index trees.

Each level within the hierarchy may perform the following operations:(1) Tree balancing to optimize lookup time; (2) Reference count andaging to determine when blocks are moved between different storage; (3)Free list updating for each local level of hierarchy as well as keepinga parameters of fill level of the major levels of the local hierarchy;(4) Delivering periodic fill levels to the next level of hierarchy toenable load balancing of storage between DIMMs on a local server andbetween levels of object memory fabric hierarchy; (5) If a Router, thenload balancing between child nodes.

Block reference count may be utilized object memory fabric to indicatethe relative frequency of access. Higher value may indicate morefrequent use over time, lower less frequent use. When block referencecount is associated with a block in persistent memory, blocks which havelowest values may be candidates to move to another DIMM or node that hasmore available space. Each time a block is accelerated into volatilememory, the reference count may be incremented. Low frequency backgroundscanning may decrement the value if it is not in volatile memory andincrements the value if it is in volatile memory. It may be expectedthat the scanning algorithm may evolve over time to increment ordecrement based or reference value to provide appropriate hysteresis.Blocks that are frequently accelerated into or present in volatilememory may have higher reference count values.

When a block reference count is associated with a block in volatilememory, blocks which have lowest values may be candidates to move backto persistent memory or memory within another DIMM or node. When a blockmoves into volatile memory, reference count may be initialized based onthe instruction or use case that initiated the movement. For example, ademand miss may set the value to a midpoint, and a speculative fetch mayset it to a quarter point. Single use may set it to below the quarterpoint. Moderate frequency background scanning may decrement thereferenced value. Thus, demand fetches may be initially weighted higherthan speculative fetches. If a speculative fetch is not utilized, it mayquickly fall to the lower referenced values that may be replaced first.Single use may be weighted low to be candidate for replacement soonerthan other blocks. Thus, single use and speculative blocks may notreplace other frequently accessed blocks.

FIG. 16 is a block diagrams illustrating an aspect of example physicalmemory organization 1600, in accordance with certain embodiments of thepresent disclosure. Object memory fabric may provide multiple methods toaccess objects and blocks. For example, a direct method may be based onexecution units within object memory fabric or devices that can directlygenerate full 128-bit memory fabric addresses may have full directaccess.

An associated method may consider conventional servers having limitedvirtual address and physical address spaces. Object memory fabric mayprovide an API to dynamically associate objects (e.g., segments) andblocks (e.g., pages) with the larger object memory fabric 128-bit memoryfabric address. The associations provided by AssocObj and AssocBlkoperations may be utilized by object memory fabric driver (e.g., Linuxdriver) and object memory fabric system library (Syslib) interfacingwith the standard processor memory management to enable object memoryfabric to behave transparently to both the operating system andapplications. Object memory fabric may provide: (a) an API to associatea processor segment and its range of virtual addresses with an objectmemory fabric object thus ensuring seamless pointer and virtualaddressing compatibility; (b) an API to associate a page of virtualaddress space and the corresponding object memory fabric block with apage/block of local physical memory within an object memory fabric DIMM(which may ensure processor memory management and physical addressingcompatibility); and/or (c) local physical memory divided into standardconventional server DIMM slots, with 512 Gbytes (2³⁹ bytes) per DIMMslot. On a per slot basis, object memory fabric may keep an additionaldirectory indexed by physical address of the object memory fabricaddress of each block that has been associated with the correspondingphysical address as illustrated in the following diagram.

FIG. 16 is a block diagram illustrating an example physical memoryorganization 1600, in accordance with certain embodiments of the presentdisclosure. A physical memory directory 1605 for physical memory 1630may include: object memory fabric object block address 1610; object size1615; reference count 1620; a modified field 1625 which may indicatewhether the block has been modified with respect to persistent memory;and/or write enable 1630 which may indicate whether local block cachestate is sufficient for writing. For example, if the cache state werecopy, writes may be blocked, and object memory fabric would may withsufficient state for writing. The physical address range may be assignedto each by system BIOS on boot based object memory fabric DIMM SPD(Serial Presence Detect) configuration.

FIG. 17A is a block diagram illustrating an example object addressing1700, in accordance with certain embodiments of the present disclosure.FIG. 17B is a block diagram illustrating example aspects of objectmemory fabric pointer and block addressing 1750, in accordance withcertain embodiments of the present disclosure. Object memory fabricobjects 1705 may include object data 1710 and metadata 1715, bothdivided into 4k blocks in some embodiments as one unit of storageallocation, referenced by the object memory fabric address space 1720.The object starting address may be the ObjectID 1755. Data 1710 may beaccessed as a positive offset from ObjectID 1755. The largest offset maybe based on ObjectSize 1760.

Object metadata 1715 may be accessed as a negative offset fromObjectStart 1725 (ObjectID). Metadata 1715 can be also referenced by anobject memory fabric address in the top 1/16th of object address space1720. The start of a specific objects metadata may be2¹²⁸-2¹²⁴+ObjStart/16. This arrangement may enable the POIT to compactlyrepresent metadata 1715 and the metadata 1715 to have an object addressspace so it can be managed coherently just like data. Although the fullobject address space may be allocated for object data 1710 and metadata1715, storage may be sparsely allocated on a block basis. At a minimum,an object 1705 has a single block of storage allocated for the firstblock of metadata 1715, in some embodiments. Object access privilege maybe determined through object memory fabric Filesystem ACL or the like.Since object memory fabric manages objects in units of 4k blocks,addressing within the object memory fabric object memory are blockaddresses, called Block Object Address 1765 (BOA), which corresponds toobject address space [127:12]. BOA [11:0] may be utilized by the objectmemory for ObjectSize (BOA[7:0]) and object metadata indication(BOA[2:0])

FIG. 18 is a block diagram illustrating example aspects 1800 of objectmetadata 1805, in accordance with certain embodiments of the presentdisclosure. Table 6 below indicates metadata of the first block 1810 ofmetadata 1805 per certain embodiments. In some embodiments, the firstblock 1810 of metadata 1805 may hold metadata for an object as depicted.

TABLE 6 Metadata First Block Name Description Size Object address ObjectID. Number of significant bits 16 space determined by object size Objectsize Object Size CRC Reserved for optional object crc 16 Parity pointerPointer to pages used for optional 16 object block parity CompressionFlags OID of compression object 16 Encryption Flags OID of encryptionobject 16 System Defined Reserved for software defined OS functions 256Application Reserved for software defined owning 256 Defined applicationfunctions Others 432 Remote Specifies Objects accessible from thisobject. 1024 Object Table Specifies 64 OIDs (128 bit). The zero entry isused to specify object or metadata within this Triggers Triggers orTrigger B-Tree root 2048 4096

System-defined metadata may include any Linux-related data to coordinateuse of certain objects seamlessly across servers. Application-definedmetadata may include application related data from a file system ordatabase storage manager to enable searches and/or relationships betweenobjects that are managed by the application.

For an object with a small number of triggers, base triggers may bestored within the first block; otherwise, a trigger B-tree root mayreference metadata expansion area for the corresponding object. TriggerB-tree leaf may specify base triggers. A base trigger may be a singletrigger action. When greater than a single action is required, a triggerprogram may be invoked. When trigger programs are invoked, they mayreside in the expansion area. The remote object table may specifyobjects that are accessible from this object by the extended instructionset.

Certain embodiments may provide for an extended instruction executionmodel. One goal of the extended execution model may be to provide alightweight dynamic mechanism to provide memory and executionparallelism. The dynamic mechanism enables a dataflow method ofexecution that enables a high degree of parallelism combined withtolerance of variation in access delay of portion of objects. Work maybe accomplished based on the actual dependencies, not a single accessdelay holding up the computation.

Various embodiments may include one or a combination of the following.Loads and memory references may be split transactions, with separaterequest and response so that the thread and memory path are not utilizedduring the entire transaction. Each thread and execution unit may beable to issue multiple loads into object memory fabric (local andremote) prior to receiving a response. Object memory fabric may be apipeline to handle multiple requests and responses from multiple sourcesso that memory resources can be fully utilized. The execution unit maybe able to accept responses in a different order from that the requestswere issued. Execution units can switch to different threads to be fullyutilized. Object memory fabric can implement policies to dynamicallydetermine when to move objects or portions of objects versus moving athread versus creating a thread.

FIG. 19 is a block diagram illustrating aspects of an examplemicro-thread model 1900, in accordance with certain embodiments of thepresent disclosure. A thread may be the basic unit of execution. Athread may be defined at least in part by an instruction pointer (IP)and a frame pointer (FP). The instruction pointer may specify thecurrent instruction that is being executed. The frame pointer mayspecify the location of the current execution state of the thread.

A thread can include multiple micro-threads. In the example depicted,the thread 1905 include micro-threads 1906 and 1907. However, a threadcan include greater numbers of micro-threads. The micro-threads of aparticular thread may share the same frame pointer but have differentinstruction pointers. In the example depicted, frame pointers 1905-1 and1905-2 specify the same location, but instruction pointers 1910 and 1911specify different instructions.

One purpose of micro-threads may be to enable data-flow like operationwithin a thread by enabling multiple asynchronous pending memoryoperations. Micro-threads may be created by a version of the forkinstruction and may be rejoined by the join instruction. The extendedinstruction set may treat the frame pointer as a top of stack orregister set by performing operations on offsets from the frame pointer.Load and store instructions may move data between the frame and theobject.

FIG. 20 is a block diagram illustrating aspects of an examplerelationship 2000 of code, frame, and object, in accordance with certainembodiments of the present disclosure. Specifically, FIG. 20 illustrateshow object data 2005 is referenced through the frame 2010. The defaultmay be for load and store instructions to reference the object 2005within local scope. Access to object 2005 beyond local scope can begiven in a secure manner by access control and security policies. Oncethis access is given, objects 2005 within local and non-local scope canbe accessed with equal efficiency. Object memory fabric encouragesstrong security by encouraging efficient object encapsulation. Bysharing the frame, micro-threads provide a very lightweight mechanism toachieve dynamic and data-flow memory and execution parallelism, forexample, on the order of 10-20 micro-threads or more. The multiplethreads enable virtually unlimited memory based parallelism.

FIG. 21 is a block diagram illustrating aspects of an example ofmicro-thread concurrency 2100, in accordance with certain embodiments ofthe present disclosure. Specifically, FIG. 21 illustrates the paralleldata-flow concurrency for a simple example of summing several randomlylocated values. A serial version 2105 and a parallel version 2110 arejuxtaposed, in accordance with certain embodiments of the presentdisclosure. The parallel version 2110 can be almost n times faster sinceloads are overlapped in parallel.

Referring again to FIG. 20, the approach can be extended to interactiveand recursive approaches in a dynamic manner. The advantages ofprefetching ahead can now be achieved in cases with minimal localitywithout using prefetch. When an object is created, a single defaultthread 2015 (single micro-thread 2020 is created) may be waiting tostart with a start message to the default thread 2015. The defaultthread 2015 then can create micro-threads with the thread or use aversion of the fork instruction to create a new thread.

In some embodiments, both the instruction pointer and the frame pointermay be restricted to the expansion metadata region 1815 starting atblock two and extending to SegSize/16. As the number of objects, objectsize, and object capacity increase, the thread and micro-threadparallelism may increase. Since threads and micro-threads may be tied toobjects, as objects move and distribute so may the threads andmicro-threads. Embodiments of object memory fabric may have the dynamicchoice of moving objects or portions of objects to threads ordistributing threads to the object(s). This may be facilitated by theencapsulated object methods implemented by the extended execution model.

As further noted above, embodiments of the present invention may alsoinclude an object memory fabric instruction set which can provide aunique instruction model based on triggers that support core operationsand optimizations and allow the memory intensive portion of applicationsto be more efficiently executed in a highly parallel manner within theobject memory fabric.

The object memory fabric instruction set can be data-enabling due toseveral characteristics. First, the sequence of instructions can betriggered flexibly by data access by a conventional processor, objectmemory fabric activity, another sequence or an explicit object memoryfabric API call. Second, sequences can be of arbitrary length, but shortsequences can be more efficient. Third, the object memory fabricinstruction set can have a highly multi-threaded memory scale. Fourth,the object memory fabric instruction set can provide efficientco-threading with conventional processors.

Embodiments of the present invention include two categories ofinstructions. The first category of instructions is triggerinstructions. Trigger instructions include a single instruction andaction based on a reference to a specific Object Address (OA). A triggerinstruction can invoke extended instructions. The second category ofinstructions is extended instructions. Extended instructions definearbitrary parallel functionality ranging from API calls to complete highlevel software functions. After a discussion of the instruction setmodel, these two categories of instructions will be discussed in turn.As noted, trigger instructions enable efficient single purpose memoryrelated functions with no context outside of the trigger.

Using the metadata and triggers defined above an execution model basedon memory data flow can be implemented. This model can represent adynamic dataflow method of execution in which processes are performedbased on actual dependencies of the memory objects. This provides a highdegree of memory and execution parallelism which in turn providestolerance of variations in access delays between memory objects. In thismodel, sequences of instructions are executed and managed based on dataaccess. These sequences can be of arbitrary length but short sequencesare more efficient and provide greater parallelism.

The extended instruction set enables efficient, highly threaded,in-memory execution. The instruction set gains it's efficiency inseveral manners. First, the instruction set can include direct objectaddress manipulation and generation without the overhead of complexaddress translation and software layers to manage differing addressspaces. Second, the instruction set can include direct objectauthentication with no runtime overhead that can be set based on securethird party authentication software. Third, the instruction set caninclude object related memory computing. For example, as objects move,the computing can move with them. Fourth, the instruction set caninclude parallelism that is dynamic and transparent based on scale andactivity. Fifth, the instruction set can include an object memory fabricoperation that can be implemented with the integrated memory instructionset so that memory behavior can be tailored to application requirements.Sixth, the instruction set can handle functionality for memory-intensivecomputing directory in the memory. This includes adding operations asmemory is touched. Possible operations may include, but are not limitedto, searching, image/signal processing, encryption, and compression.Inefficient interactions with conventional processors are significantlyreduced.

The extended instruction capability can be targeted at memory intensivecomputing which is dominated with memory references for interesting sizeproblems that are larger than caches or main memory, and simpleoperations based on these references. Some examples can include but arenot limited to:

-   -   Defining API macros from conventional processors.    -   Defining the streams of interaction between hierarchical        components of the object memory fabric. Each component can use a        core set of instruction sequences to implement object memory        fabric functionality.    -   Short sequences for macros to accelerate key application kernels        such as BFS (Breath First Search), etc. BFS is a core strategy        for searching a graph and is heavily used by graph databases and        graph applications. For example, BFS is used across a wide        variety of problem spaces to find a shortest or optimal path. It        is a representative algorithm that illustrates the challenges        for analyzing large scale graphs namely, no locality because        graphs are larger than caches and main memory and virtually all        the work is through memory references. In the case of BFS, the        extended instruction capability described herein coupled with        threads handles almost the entire BFS by recursive instantiation        of threads to search adjacency lists based on graph size and        available nodes. Highly parallel direct in-memory processing and        high-level memory operations reduce software path-length. When        combined with object memory fabric capability described above to        bring all data in-memory and localize it ahead of use, the        performance and efficiency per node is significantly increased.    -   Complete layer functionality, such as:        -   Storage engine for hierarchical file system built on top of            a flat object memory. A storage engine is, for example, what            stores, handles, and retrieves the appropriate object(s) and            information from within an object. For MySQL, the object may            be a table. For a file system, the object may be a file or            directory. For a graph database, the object may be a graph            and information may consist of vertices and edges. Operators            supported may be, for example, based on type of object            (file, graph, SQL, etc.).        -   Storage engine for structured database such as MySQL        -   Storage engine for unstructured data such as graph database        -   Storage engine for NoSQL key-value store    -   Complete application: Filesystem, structured database such as        MySQL, unstructured data such as graph database or NoSQL        key-value store    -   User programmable.

According to one embodiment, a base trigger may invoke a single triggeraction based on reference to a specific OA. There can be a single basetrigger per OA. When greater than a single action is required, a triggerprogram can be invoked with the TrigFunction base trigger. Base triggersmay consist of the instructions included in Table 7 below.

TABLE 7 Example Base Trigger Instruction Set Base Trigger DescriptionTrigger Fetch the block specified in the pointer at the specified objectoffset based on specified trigger conditions and actions TrigFunctionExecute the trigger program starting at specified meta-data offset whenthe specified data obj ect offset and specified trigger conditions.

As noted, the Trigger instruction set can include fetching the blockspecified in the pointer at the specified object offset based on thespecified trigger conditions and actions. The Trigger instruction binaryformat can be expressed as:

Trigger PtrType TrigType TrigAction RefPolicy ObjOffset

An example set of operands for the Trigger instruction set are includedin Tables 8-12 below.

TABLE 8 PrtType-Pointer Type Encoding Symbol Description None No pointerOA Object Address ObjReg Object Relative ObjVA Object Virtual AddressReserved Reserved

TABLE 9 TrigType-Trigger Type Encoding Symbol Description None demandTrigger by demand miss for block prefetch Trigger by preached blockaccess Triggered by actual processor access to cache block emptyfillTrigger by empty or fill instructions. Enables trigger on specificprocessor action any Any trigger type reserved Reserved

TABLE 10 TrigAction-Trigger Action Encoding Symbol Description NoneCache Trigger by demand miss for block Clean Trigger by preached blockreserved Triggered by actual processor access to cache block

TABLE 11 RefPolicy-Reference Count and Policy Encoding SymbolDescription InitLowA Initial reference count of prefetch page to lowvalue, policy A InitMidA Initial reference count of prefetch page to midvalue, policy A InitHighA Initial reference count of prefetch page tohigh value, policy A InitLowB Initial reference count of prefetch pageto low value, policy B InitMidB Initial reference count of prefetch pageto mid value, policy B InitHighB Initial reference count of prefetchpage to high value, policy B

TABLE 12 ObjOffset-Object Offset Description Object offset based onObject size. Trigger can be evaluated based on TriggerType and triggeraction taken if TriggerType is satisfied is define by TriggerAction andRefPolicy.

As noted, the TrigFunction (or TriggerFunct) instruction set can includeexecuting the trigger program starting at specified meta-data offsetwhen the specified data object offset and specified trigger conditions.TriggerFunct can enable more complex sequences than a single Triggerinstruction to be executed. The TrigFunct Instruction binary format canbe expressed as:

TrigFunct PtrType TrigType MetaDataOffset ObjOffset

An example set of operands for the Trigger instruction set are includedin Tables 13-16 below.

TABLE 13 PrtType-Pointer Type Encoding Symbol Description None Nopointer OA Object Address ObjReg Object Relative ObjVA Object VirtualAddress Reserved Reserved

TABLE 14 TrigType-Trigger Type Encoding Symbol Description None demandTrigger by demand miss for block prefetch Trigger by preached blockaccess Triggered by actual processor access to cache block emptyfillTrigger by empty or fill instructions. Enables trigger on specificprocessor action any Any trigger type reserved Reserved

TABLE 15 MetaDataOffset-Meta-Data Offset Description Meta-Data offsetbased on Object size. TriggerFunction can be evaluated based onTriggerType. The trigger program starting at MetaDataOffset is executedif TriggerType is satisfied.

TABLE 16 ObjOffset-Object Offset Description Object offset based onObject size. TriggerFunction can be evaluated based on TriggerType atObj Offset. The trigger program starting at MetaDataOffset is executedif TriggerType is satisfied.

According to one embodiment, extended instructions can be interpreted in64 bit word chunks in 3 formats, including short (2 instructions perword), long (single instruction per word), and reserved.

TABLE 17 Extended Instruction Format Format bits[63:62] bits[61:31]bits[30:0] Short 0x00 s_instruction[1] (31 bits) s_instruction[0] (31bits) Long 0x01 l_instruction (62 bits) Reserved 0x1*

Generally speaking, triggers in combination with the extendedinstruction set can be used to define arbitrary, parallel functionalitysuch as: direct object address manipulation and generation without theoverhead of complex address translation and software layers to managediffering address space; direct object authentication with no runtimeoverhead that can be set based on secure 3rd party authenticationsoftware; object related memory computing in which, as objects movebetween nodes, the computing can move with them; and parallelism that isdynamically and transparent based on scale and activity. Theseinstructions are divided into three conceptual classes: memory referenceincluding load, store, and special memory fabric instructions; controlflow including fork, join, and branches; and execute includingarithmetic and comparison instructions.

A list of the different types of memory reference instructions are shownin Table 18 below.

TABLE 18 Memory Reference Instructions [30:23] Encoding/ [22:17] [16:11][10:5] [4:0] Instruction Options FPA FPB FPC Predicate Pull encode[7:0]oid offset prior, src_pred plstate Push encode[7:0] oid offset prior,src_pred plstate Ack encode[7:0] oid offset src_pred Load encode[4:0],src oid src offset dst fp src_pred osize[2:0] Store encode[4:0], dst oiddst offset src fp src_pred osize[2:0] ReadPA encode[7:0] src pa dst fpsrc_pred WritePA encode[7:0] dst pa src fp src_pred Empty encode[7:0]src oid src offset dst fp src_pred Fill encode[7:0] dst oid dst offsetsrc fp src_pred Pointer encode[5:0], dst oid dst offset src_predopt[1:0] PrePtrChn encode[4:0], src oid src offset src offset src_predopt[2:0] st end ScanEF encode[4:0], src oid src offset dst fp src_predopt[2:0] Create src_pred CopyObj src_pred CopyBlk src_pred Allocatesrc_pred Deallocate src_pred Destroy src_pred Persist src_pred AssocObjsrc_pred DeAssocObj src_pred AssocBlk encode[5:0], src oid src pa dst lssrc_pred opt[1:0] DeAssocBlk encode[7:0] src_pred OpenObj src_predOpenBlk src_pred Btree src_pred

The pull instruction may be utilized within the object memory fabric asa request to copy or move the specified block to (e.g. local) storage.The 4k byte block operand in the object specified by src_oid at theobject offset specified by src_offset may be requested with the statespecified by pull_state with the priority specified by priority. Thedata may be subsequently moved by a push instruction. The Pullinstruction binary format can be expressed as:

Pull Instruction (binary format) [30:23] [22:17] [16:11] [10:9] [8:5][4:0] src_oid src_offset priority pull_state Predicate

An example set of operands for the Pull instruction set are included inTables 19-23 below.

TABLE 19 predicate-Predicate Description Specifies a single bitpredicate register. If the predicate value is true, the instructionexecutes, if false the instruction does not execute.

TABLE 20 src_oid—Source Object Identifier Description Index into theremote object table to specify the specific object identifier for thismemory operation. Index value of 0 always corresponds to local object.

TABLE 21 src_off—Source Object Offset Description Specifies the unsignedoffset from the thread frame pointer to read the source operandcorresponding to the object offset.

TABLE 22 priority—How object memory fabric treats the requests EncodingSymbol Description 0x0 required-high Highest priority handling ofrequests. Highest priority requests are always handled in the orderreceived. 0x1 required-low Can be optionally reordered with respect torequired-high by object memory fabric only to prioritize required-highrequests for short time periods. Must be completed. Typically mostrequests are of required-low priority. 0x2 optional-high Requests can beconsidered optional by object memory fabric and can be delayed ordeleted as required to manage object memory fabric load. Optionalhighrequests are always considered ahead of optional-low requests. 0x3optional-low Request can be considered optional by object memory fabricand can be delayed or deleted as required to manage object memory fabricload. Optional-low requests are treated at the lowest priority.Typically most optional requests are of the optional-low priority.

TABLE 23 pull_state—Requested object memory fabric state for blockStates can be listed in order of weakest to strongest. State can bereturned in a stronger state. Modified with respect to persistent memorycan be indicated by _m suffix. Encoding Symbol Description 0x0 invalid0x1 snapcopy Snapshot copy. This copy can be updated when a block ispersisted. Utilized for object fault tolerance. Can be configured on anobject basis redundancy and geographic dispersion. 0x2 shadcopy Shadowcopy. Can be updated on a lazy basis (eventually consistent), usuallyafter a period of time or some number of writes and/or transactions. Canalso be used for fault tolerant block copies. 0x3 copy Read-only copy.Will be updated for owner modifications as they occur. Insuressequential consistency. 0x4 own_snapcopy Exclusive owner with snapshotcopy. 0x8 own-snapcopy_m Enables local write privilege without anyupdates required. Snapshot copies may exist, but are only updated whencorresponding block is persisted and through and push instruction withpush_state = pstate_sncopy. 0x5 own_shadcopy Non-exclusive owner withshadow copies. 0x9 own-shadcopy_m Enables write privilege shadow copiesor snapshot copies to exist which are updated from writes on a lazybasis—eventually consistent. 0x6 own_copy Non-exclusive owner withcopies. Enables 0xa own_copy_m write privilege and copies, shadow copiesor snapshot copies to exist which are updated from writes. Multiplewrites to the same block can occur with a single update. 0x7 ownExclusive owner. Enables local write 0xb own_m privilege. No copies,shadow copies or snapshot copies exist. 0xc error Error has beenencountered on corresponding block. 0xd-0xf reserved Reserved

Push instruction may be utilized to copy or move the specified blockfrom local storage to a remote location. The 4k byte block operand inthe object specified by src_oid at the object offset specified bysrc_offset may be requested with the state specified by pull_state withthe priority specified by priority. The data may be previously requestedby a pull instruction. The Push instruction binary format can beexpressed as:

Push Instruction (binary format) [30:23] [22:17] [16:11] [10:9] [8:5][4:0] src_oid src_offset priority push_state Predicate

An example set of operands for the Push instruction set are included inTables 24-28 below.

TABLE 24 predicate—Predicate Description Specifies a single bitpredicate register. If the predicate value is true, the instructionexecutes, if false the instruction does not execute.

TABLE 25 src_oid—Source Object Identifier Description Index into theremote object table to specify the specific object identifier for thismemory operation. Index value of 0 always corresponds to local object.

TABLE 26 src_off—Source Object Offset Description Specifies the unsignedoffset from the thread frame pointer to read the source operandcorresponding to the object offset.

TABLE 27 priority—How object memory fabric treats the requests EncodingSymbol Description 0x0 required-high Highest priority handling ofrequests. Highest priority requests are always handled in the orderreceived. 0x1 required-low Can be optionally reordered with respect torequired-high by object memory fabric only to prioritize required-highrequests for short time periods. Must be completed. Typically mostrequests are of required-low priority. 0x2 optional-high Requests can beconsidered optional by object memory fabric and can be delayed ordeleted as required to manage object memory fabric load. Optional-highrequests are always considered ahead of optional-low requests. 0x3optional-low Request can be considered optional by object memory fabricand can be delayed or deleted as required to manage object memory fabricload. Optional-low requests are treated at the lowest priority.Typically most optional requests are of the optional-low priority.

TABLE 28 push_state—Requested object memory fabric state for blockModified with respect to persistent memory can be indicated by _msuffix. Encoding Symbol Description 0x0 invalid 0x1 snapcopy Snapshotcopy. This copy can be updated when a block is persisted. Utilized forobject fault tolerance. Can be configured on an object basis redundancyand geographic dispersion. 0x2 shadcopy Shadow copy. Will be updated ona lazy basis—eventually consistent, usually after a period of time orsome number of writes and/or transaction. Can also be used for faulttolerant block copies. 0x3 copy Read-only copy. Can be updated for ownermodifications as they occur. Insures sequential consistency. 0x4own_snapcopy Exclusive owner with snapshot copy. 0x8 own_snapcopy_mEnables local write privilege without any updates required. Snapshotcopies may exist, but are only updated when corresponding block ispersisted and through and push instruction with push_state =pstate_sncopy. 0x5 own_shadcopy Non-exclusive owner with shadow 0x9own_shadcopy_m copies. Enables write privilege shadow copies or snapshotcopies to exist which are updated from writes on a lazy basis—eventuallyconsistent. 0x6 own_copy Non-exclusive owner with copies. Enables 0xaown_copy_m write privilege and copies, shadow copies or snapshot copiesto exist which are updated from writes. Multiple writes to the sameblock can occur with a single update. 0x7 own Exclusive owner. Enableslocal write 0xb own_m privilege. No copies, shadow copies or snapshotcopies exist. 0xc error Error has been encountered on correspondingblock. 0xd-0xf reserved

PushAck or Ack instruction may be utilized to acknowledge that the blockassociated with a Push has been accepted at one or more locations. The4k byte block operand in the object specified by src_oid at the objectoffset specified by src_offset may be acknowledged. The Ack instructionbinary format can be expressed as:

Ack Instruction (binary format) [30:23] [22:17] [16:11] [10:9] [8:5][4:0] src_oid src_offset Predicate

An example set of operands for the Push instruction set are included inTables 29-31 below.

TABLE 29 predicate—Predicate Description Specifies a single bitpredicate register. If the predicate value is true, the instructionexecutes, if false the instruction does not execute.

TABLE 30 src_oid—Source Object Identifier Description Index into theremote object table to specify the specific object identifier for thismemory operation. Index value of 0 always corresponds to local object.

TABLE 31 src_off—Source Object Offset Description Specifies the unsignedoffset from the thread frame pointer to read the source operandcorresponding to the object offset.

The Load instruction set includes the osize operand in the objectspecified by src_oid at the object offset specified by src_offset.src_offset can be written to the word offset from the frame pointerspecified by dst_fp. The load instruction ignores the empty state.

Load Instruction (binary format) [30:26] [25:23] [22:17] [16:11] [10:5][4:0] osize src_oid src_offset dst_fp Predicate

An example set of operands for the Load instruction set are included inTables 32-36 below.

TABLE 32 osize-Object operand size Encoding Symbol Description 0x0  8bit unsigned 8 bit source is zero extended to 64 bit dst_fp 0x1 16 bitunsigned 16 bit source is zero extended to 64 bit dst_fp 0x2 32 bitunsigned 32 bit source is zero extended to 64 bit dst_fp 0x3 64 bit 64bit source is loaded into 64 bit dst_fp 0x4  8 bit signed 8 bit sourceis sign extended to 64 bit dst_fp 0x5 16 bit signed 16 bit source issign extended to 64 bit dst_fp 0x6 32 bit signed 32 bit source is signextended to 64 bit dst_fp 0x7 reserved

TABLE 33 predicate-Predicate Description Specifies a single bitpredicate register. If the predicate value is true, the instructionexecutes, if false the instruction does not execute.

TABLE 34 src_oid-Source Object Identifier Description Index into theremote object table to specify the specific object identifier for thismemory operation. Index value of 0 always corresponds to local object.

TABLE 35 src_off-Source Object Offset Description Specifies the unsignedoffset from the thread frame pointer to read the source operandcorresponding to the object offset.

TABLE 36 dst_fp-Destination offset from frame pointer DescriptionSpecifies the unsigned offset from the thread frame pointer to write thesource operand.

The Store instruction set includes the word specified by src_fp can betruncated to the size specified by osize and stored into the objectspecified by dst_oid at offset of dst_offst. For example, only the ssizebytes are stored. The store instruction ignores the empty state. TheStore instruction binary format can be expressed as:

Store Instruction (binary format) [30:25] [24:23] [22:17] [16:11] [10:5][4:0] ssize dst_oid dst_offset src_fp Predicate

An example set of operands for the Store instruction set are included inTables 37-41 below.

TABLE 37 ssize-Store Object operand size Encoding Symbol Description 0x0 8 bit Least significant 8 bits are stored 0x1 16 bit Least significant16 bits are stored 0x2 32 bit Least significant 32 bits are stored 0x364 bit Least significant 64 bits are stored

TABLE 38 predicate-Predicate Description Specifies a single bitpredicate register. If the predicate value is true, the instructionexecutes, if false the instruction does not execute.

TABLE 39 dst_oid-Source Object Identifier Description Index into theremote object table to specify the specific object identifier for thismemory operation. Index value of 0 always corresponds to local object.

TABLE 40 dst_off-Source Object Offset Description Specifies the unsignedoffset from the thread frame pointer to read the source operandcorresponding to the object offset.

TABLE 41 src_fp-Destination offset from frame pointer DescriptionSpecifies the unsigned offset from the thread frame pointer to read thesource operand.

The ReadPA instruction reads 64 bytes by physical address of the localmemory module. The operand in the object specified by src_pa can bewritten to the word offset from the frame pointer specified by dst_fp.The ReadPA instruction binary format can be expressed as:

ReadPA Instruction (binary format) [30:26] [25:23] [22:17] [16:11][10:5] [4:0] src_pa dst_fp Predicate

An example set of operands for the ReadPA instruction set are includedin Tables 42-44 below.

TABLE 42 predicate-Predicate Description Specifies a single bitpredicate register. If the predicate value is true, the instructionexecutes, if false the instruction does not execute.

TABLE 43 src_pa-Source Physical Address Description Specifies a physicaladdress local to the current node/server.

TABLE 44 dst_fp-Destination offset from frame pointer DescriptionSpecifies the unsigned offset from the thread frame pointer to write thesource operand.

The WritePA instruction writes 64 bytes by physical address of the localmemory module. The 64 bytes specified by src_fp is stored into thephysical address specified by dst_pa. The ReadPA instruction binaryformat can be expressed as:

WritePA Instruction (binary format) [30:25] [24:23] [22:17] [16:11][10:5] [4:0] dst_pa src_fp Predicate

An example set of operands for the WritePA instruction set are includedin Tables 45-47 below.

TABLE 45 predicate-Predicate Description Specifies a single bitpredicate register. If the predicate value is true, the instructionexecutes, if false the instruction does not execute.

TABLE 46 dst_pa-Destination physical address Description Specifies aphysical address local to the current node/server

TABLE 47 src_fp-Source frame pointer Description Specifies the unsignedoffset from the thread frame pointer to read the source operand.

Each word within a object memory fabric object can include an state toindicate empty or full states. An empty state conceptually means thatthe value of the corresponding word has been emptied. A full stateconceptually means the value of the corresponding word has been filled.This state can be used by certain instructions to indivisibly insurethat only a single thread can read or write the word. Empty instructionscan operate similar to a load, as shown below in Table 48.

TABLE 48 State Result Empty Memory doesn't respond until wordtransitions to full state Full Completes as load and indivisiblytransitions state to empty

The osize operand in the object specified by src_oid at the objectoffset specified by src_offset can be written to the word offset fromthe frame pointer specified by dst_fp. The Empty instruction binaryformat can be expressed as:

Empty Instruction (binary format) [30:26] [25:23] [22:17] [16:11] [10:5][4:0] src_oid src_offset dst_fp Predicate

An example set of operands for the Empty instruction set are included inTables 49-52 below.

TABLE 49 predicate-Predicate Description Specifies a single bitpredicate register. If the predicate value is true, the instructionexecutes, if false the instruction does not execute.

TABLE 50 src_oid-Source Object Identifier Description Index into theremote object table to specify the specific object identifier for thismemory operation. Index value of 0 always corresponds to local object.

TABLE 51 src_off-Source Object Offset Description Specifies the unsignedoffset from the thread frame pointer to read the source operandcorresponding to the object offset.

TABLE 52 dst_fp-Destination offset from frame pointer DescriptionSpecifies the unsigned offset from the thread frame pointer to write thesource operand.

Each word within a memory fabric object can include an state to indicateempty or full states. Empty state conceptually means that the value ofthe corresponding word has been emptied. Full state conceptually meansthe value of the corresponding word has been filled. This state can beused by certain instructions to indivisibly insure that only a singlethread can read or write the word. The Fill instruction binary formatcan be expressed as:

Fill Instruction (binary format) [30:25] [24:23] [22:17] [16:11] [10:5][4:0] dst_oid dst_offset src_fp Predicate

Fill instruction operates similar to a store, as shown below in Table53.

TABLE 53 State Result Empty The fill instruction completes as a storeand transitions state to full. Full The fill instruction

The word specified by src_fp can be stored into the object specified bydst_oid at offset of dst_offst. Only the ssize bytes are stored. Storeignores empty state. An example set of operands for the Fill instructionset are included in Tables 54-57 below.

TABLE 54 predicate-Predicate Description Specifies a single bitpredicate register. If the predicate value is true, the instructionexecutes, if false the instruction does not execute.

TABLE 55 dst_oid-Source Object Identifier Description Index into theremote object table to specify the specific object identifier for thismemory operation. Index value of 0 always corresponds to local object.

TABLE 56 dst_off-Source Object Offset Description Specifies the unsignedoffset from the thread frame pointer to read the source operandcorresponding to the object offset.

TABLE 57 src_fp-Destination offset from frame pointer DescriptionSpecifies the unsigned offset from the thread frame pointer to read thesource operand.

The Pointer instruction set can specify to the object memory fabric thata pointer of ptr_type can be located in the object specified by scrod atobject offset specified by src_offset. This information can be utilizedby the object memory fabric to pre-stage data movement. The Pointerinstruction binary format can be expressed as:

Pointer Instruction (binary format) [30:26] [24:23] [22:17] [16:11][10:5] [4:0] ptr_type src_oid src_offset Predicate

An example set of operands for the Pointer instruction set are includedin Tables 58-61 below.

TABLE 58 ptr_type-Pointer Type Encoding Symbol Description 0x0 none Nopointer at this object offset 0x1 MF Address Full 128 Memory FabricAddress pointer at this object offset 0x2 Object Relative 64 bit objectrelative pointer at this object offset. The range of the object relativepointer can be determined by object size 0x3 Object-VA 64 bit objectvirtual address pointer at this object offset. The range of the objectrelative pointer can be determined by object size.

TABLE 59 predicate-Predicate Description Specifies a single bitpredicate register. If the predicate value is true, the instructionexecutes, if false the instruction does not execute.

TABLE 60 src_oid-Source Object Identifier Description Index into theremote object table to specify the specific object identifier for thismemory operation. Index value of 0 always corresponds to local object.

TABLE 61 src_off-Source Object Offset Description Specifies the unsignedoffset from the thread frame pointer to read the source operandcorresponding to the object offset.

The Prefetch Pointer Chain instruction set can be based on the policyspecified by policy in the object specified by src_oid, in the rangespecified by src_offset_st to src_offset end. The osize operand in theobject specified by src_oid at the object offset specified by src_offsetcan be written to the word offset from the frame pointer specified bydst_fp. Load ignores empty state. The PrePtrChn instruction binaryformat can be expressed as:

PrePtrChn Instruction (binary format) [30:26] [25:23] [22:17] [16:11][10:5] [4:0] policy src_oid src_offset_st src_offset_end src_pred

An example set of operands for the Prefetch Pointer Chain instructionset are included in Tables 62-66 below.

TABLE 62 Policy-Prefetch PointerChain Policy Encoding Symbol Description0x0 none_ahead Just prefetch blocks corresponding to pointers in chain0x1 breath_1ahead Breath first prefetch. Fetch each pointer in chainthen fetch one ahead of each pointer 0x2 breath_2ahead Breath firstprefetch. Fetch each pointer in chain then recursively fetch two aheadof each pointer 0x3 breath_3ahead Breath first prefetch. Fetch eachpointer in chain then recursively fetch three ahead of each pointer 0x4reserved reserved 0x5 depth_1ahead Depth first prefetch 1 deep. 0x6depth_2ahead Depth first prefetch 2 deep. 0x7 depth_3ahead Depth firstprefetch 3 deep.

TABLE 63 predicate-Predicate Description Specifies a single bitpredicate register. If the predicate value is true, the instructionexecutes, if false the instruction does not execute.

TABLE 64 src_oid-Source Object Identifier Description Index into theremote object table to specify the specific object identifier for thismemory operation. Index value of 0 always corresponds to local object.

TABLE 65 src_off_st-Source Object Offset Description Specifies theunsigned offset from the thread frame pointer to read the source operandcorresponding to starting object offset..

TABLE 66 src_off_end-Destination offset from frame pointer DescriptionSpecifies the unsigned offset from the thread frame pointer to read thesource operand corresponding to ending object offset.

The Scan and Set Empty or Full instruction set can be initialed in anobject specified by src_oid, at offset specified by src_offset withspecified policy. Scan can be used to do a breath first or depth firstsearch and empty or fill the next available location. The ScanEFinstruction binary format can be expressed as:

ScanEF Instruction (binary format) [30:26] [25:23] [22:17] [16:11][10:5] [4:0] policy src_oid src_offset dst_fp Predicate

An example set of operands for the Scan and Set Empty or Fullinstruction set are included in Tables 67-71 below.

TABLE 67 osize-Object operand size Encoding Symbol Description 0x0scan_empty Scan object until empty state and set to full. Terminates onfull with null value. The object offset when the condition was met canbe placed into dst_fp. If the scan terminated without condition beingmet, a value of −0x1 can be placed into dst_fp. 0x1 scan_full Scanobject to full state and set to empty. Terminates on empty with nullvalue. The object offset when the condition was met can be placed intodst_fp. If the scan terminated without condition being met, a value of−0x1 can be placed into dst_fp. 0x2 ptr_full Follow pointer chain untilfull and set to empty. Terminates on null pointer. The object offsetwhen the condition was met can be placed into dst_fp. If the scanterminated without condition being met, a value of −0x1 can be placedinto dst_fp. 0x3 ptr_empty Follow pointer chain until empty and set tofull. Terminates on null pointer. The object offset when the conditionwas met can be placed into dst_fp. If the scan terminated withoutcondition being met, a value of −0x1 can be placed into dst_fp.

TABLE 68 predicate-Predicate Description Specifies a single bitpredicate register. If the predicate value is true, the instructionexecutes, if false the instruction does not execute.

TABLE 69 src_oid-Source Object Identifier Description Index into theremote object table to specify the specific object identifier for thismemory operation. Index value of 0 always corresponds to local object.

TABLE 70 src_off-Source Object Offset Description Specifies the unsignedoffset from the thread frame pointer to read the source operandcorresponding to the object offset.

TABLE 71 dst_fp-Destination offset from frame pointer DescriptionSpecifies the object offset when the condition was met. If the scanterminated without condition being met, a value of -0x1 can be placedinto dst_fp.

The Create instruction set includes an object memory fabric object ofthe specified Obj Size with an object ID of OA and initializationparameters of DataInit and Type. No data block storage can be allocatedand storage for the first meta-data block can be allocated. The Createinstruction binary format can be expressed as:

Create Type Redundancy ObjSize OID

An example set of operands for the Create instruction set are includedin Tables 72-75 below.

TABLE 72 Type Encoding Symbol Description volatile temp object that doesnot need to be persisted persistant object must be persisted reservedreserved

TABLE 73 Redundancy Encoding Symbol Description nonredundant Objectmemory fabric does not provide object redundancy redundant Object memoryfabric guarantees that object can be persisted in at least 2 separatenodes remote_redundant Object memory fabric guarantees that object canbe persisted in at least 2 separate nodes which are remote with respectto each other reserved reserved

TABLE 74 ObjSize-Object Size Description Specifies the object size.

TABLE 75 OID-Object Id Description Object memory fabric object ID whichalso the starting address for the object.

The CopyObj instruction set includes copies source object specified bySOID to destination object specified by DOID. If DOID is larger objectthan SOID, all DOID blocks beyond SOID size are copied as unallocated.If SOID is larger object than DOID, then the copy ends at DOID size. TheCopyObj instruction binary format can be expressed as:

CopyObj Ctype SOID DOID

An example set of operands for the CopyObj instruction set are includedin Tables 76-78 below.

76. Ctype-Copy type Encoding Symbol Description copy One time copy fromSOID to DOID. Allocated blocks are one time copied and non-allocatedblock SOID blocks become unallocated DOID blocks, object memory fabrichas the option of treating the copy initially as cow and executing thecopy in the background. cow All allocated blocks are treated as copy onwrite. Newly allocated blocks after cow are considered modified.reserved reserved

TABLE 77 SOID-Source Object ID Description Object memory fabric objectID which is the source for the copy.

TABLE 78 DOID-Destination Object ID Description Object memory fabricobject ID which is the destination for the copy.

The CopyBlk instruction set includes copies cnum source blocks startingat SourceObjectAddress (SOA) to destination starting atDestinationObjectAddress (DOA). If cnum blocks extends beyond the objectsize associated with SOA, then the undefined blocks are copied asunallocated. The CopyBlk instruction binary format can be expressed as:

CopyBlk ctype cnum SOA DOA

An example set of operands for the CopBlk instruction set are includedin Tables 79-82 below.

TABLE 79 Ctype-Copy type Encoding Symbol Description copy One time copyof cnum blocks starting at SOA to destination blocks starting at DOA.Allocated blocks are one time copied and non-allocated SOA blocks becomeunallocated SOA blocks, object memory fabric has the option of treatingthe copy initially as cow and executing the copy in the background. cowAll allocated blocks are treated as copy on write. Newly allocatedblocks after cow are considered modified. reserved reserved

TABLE 80 cnum-Number of blocks to copy Description Specifies the numberof blocks to copy.

TABLE 81 SOA-Source object memory fabric Block Object AddressDescription Object memory fabric block object address which is thesource for the copy.

TABLE 82 DOA-Destination object memory fabric Block Object AddressDescription Object memory fabric block object address which is thedestination for the copy.

The Allocate instruction set includes storage to the object specified byOID. The Allocate instruction binary format can be expressed as:

Allocate init ASize OID

An example set of operands for the Allocate instruction set are includedin Tables 83-85 below.

TABLE 83 init-Initialization Encoding Symbol Description zero Zero alldata random Random data. reserved reserved

TABLE 84 ASize-Allocation Size Encoding Symbol Description block singleblock object full object size 21 2⁹ blocks  size 30 2¹⁸ blocks size 392²⁷ blocks

TABLE 85 OID-Object ID Description Object memory fabric object ID forwhich storage is allocated.

The Deallocate instruction set includes storage for cnum blocks startingat OA. If deallocation reaches the end of the object, the operationends. The Deallocate instruction binary format can be expressed as:

Deallocate cnum OA

An example set of operands for the Deallocate instruction set areincluded in Tables 86 and 87 below.

TABLE 86 cnum-Number of blocks to copy Description Specifies the numberof blocks to deallocate.

TABLE 87 OA-Object Address Description Object memory fabric block objectaddress which is starting block number for deallocation.

The Destroy instruction set includes completely deleting all data andmeta-data corresponding to object specified by OID. The Destroyinstruction binary format can be expressed as:

Destroy OID

An example set of operands for the Destroy instruction set are includedin Table 88 below.

TABLE 88 OID-Object ID Description Object ID of the object to bedeleted.

The Persist instruction set includes persisting any modified blocks forthe specified OID. The Persist instruction binary format can beexpressed as:

Persist OID

An example set of operands for the Persist instruction set are includedin Table 89 below.

TABLE 89 OID-Object ID Description Object ID of the object to bepersisted.

The AssocObj instruction set includes associating the object OID withthe VaSegment and ProcessID. Associating an OID and VaSegment enablesObjectRelative and ObjectVA addresses to be properly accessed bytheobject memory fabric. The AssocObj instruction binary format can beexpressed as:

AssocObj OID ProcessID VaSegment

An example set of operands for the AssocObj instruction set are includedin Tables 90-92 below.

TABLE 90 OID-Object ID Description Object ID of the object to beassociated.

TABLE 91 ProcessID-Process ID Description Process ID associated with theVaSegment.

TABLE 92 OID-Object ID Description Object ID of the object to beassociated.

The DeAssocObj instruction set includes de-associating the object OIDwith the VaSegment and ProcessID. An error can be returned if theProcessID and VaSegment do not match those previously associated withthe OID. The DeAssocObj instruction binary format can be expressed as:

DeAssocObj OID ProcessID VaSegment

An example set of operands for the DeAssocObj instruction set areincluded in Tables 93-95 below.

TABLE 93 OID-Object ID Description Object ID of the object to bede-associated.

TABLE 94 ProcessID-Process ID Description Process ID associated with theVaSegment.

TABLE 95 OID-Object ID Description Object ID of the object to bede-associated.

The AssocBlk instruction set includes associating the block OA with thelocal physical address PA. This enables an Object Memory to associate anobject memory fabric block with a PA block for local processor access.The AssocBlk instruction binary format can be expressed as:

AssocBlk place OA PA LS[15:00]

An example set of operands for the AssocBlk instruction set are includedin Tables 96-99 below.

TABLE 96 place-Physical Placement Encoding Symbol Description 0x0 matchAssociate PA must match physical DIMM with allocated block. If currentlynot allocated on any physical DIMM will associate and allocate on DIMMspecified. Returns status within ack_detail package file of SUCCESS orNOT_ALLOC If not allocated the LS field provides a bitmap of currentphysical 0x1 force Force associate and implicit allocate on DIMMspecified. 0x2 dynamic Memory fabric associates a free PA with the OAand returns PA. 0x3 reserved reserved

TABLE 97 OA-object memory fabric Block Object Address Description ObjectID of the object to be associated.

TABLE 98 PA Physical block Address Description Local physical blockaddress of the block to be associated.

TABLE 99 LS[15:00]-Local State[15:00] Description Valid forackdetail::NOT_ASSOC which indicates that the OA is allocated on adifferent physical DIMM. Local state specifies a single bit indicatingwhich DIMM(s) have currently allocated the corresponding OA. Value isreturn in operand3, with bit0 corresponding to DIMM0.

The DeAssocBlk instruction set includes de-associating the block OA withthe local physical address PA. This OA will then no longer be accessiblefrom a local PA. The DeAssocBlk instruction binary format can beexpressed as:

DeAssocBlk OA PA

An example set of operands for the DeAssocBlk instruction set areincluded in Tables 100 and 101 below.

TABLE 100 OA-object memory fabric Block Object Address Description Blockobject address of block to be de-associated.

TABLE 101 PA-Physical block Address Description Local physical blockaddress of the block to be de-associated. Corresponds to Operand2 withinthe package header.

The OpenObj instruction set includes caching the object specified by OIDin the manner specified by TypeFetch and CacheMode on an advisory basis.The OpenObj instruction binary format can be expressed as:

OpenObj TypeFetch CacheMode OID

An example set of operands for the OpenObj instruction set are includedin Tables 102-104 below.

TABLE 102 OID-Object ID Description Object ID of the object to beassociated.

TABLE 103 TypeFetch-Type of Prefetch Encoding Symbol DescriptionMetaData Cache MetaData only First 8 Blocks Cache MetaData and first 8data blocks First 32 Blocks Cache MetaData and first 32 data blocksReserved Reserved

TABLE 104 CacheMode-Advisory Block State Encoding Symbol Descriptioncopy Copy block state if possible. All updates can be propagatedimmediately shadcopy Shadow copy block state if possible. Updates can bepropagated in a lazy manner snapcopy Snapshot copy. Copy only updated onpersist. own Own block state is possible. No other copies in memoryfabric owncopy Own block state with 0 or more copies if possible.own_shadcopy Own block state with 0 or more shadow copies (no copy blockstate) own_snapcopy Own block state with 0 or more snapshot copes. (nocopy or shadow copy block state)

The OpenBlk instruction set includes caching the block(s) specified byOID in the manner specified by TypeFetch and CacheMode. The prefetchterminates when its beyond the end of the object. The OpenBlkinstruction binary format can be expressed as:

OpenBlk TypeFetch CacheMode OID

An example set of operands for the OpenBlk instruction set are includedin Tables 105-107 below.

TABLE 105 OID-Object ID Description Object ID of the object to beassociated.

TABLE 106 TypeFetch-Type of Prefetch Encoding Symbol Description 1 BlockCache MetaData only First 8 Blocks Cache MetaData and 8 data blocksstarting at OID First 32 Blocks Cache MetaData and 32 data blocksstarting at OID Reserved Reserved

TABLE 107 CacheMode-Advisory Block State Encoding Symbol Descriptioncopy Copy block state if possible. All updates can be propagatedimmediately shadcopy Shadow copy block state if possible. Updates can bepropagated in a lazy manner snapcopy Snapshot copy. Copy only updated onpersist. own Own block state is possible. No other copies in memoryfabric owncopy Own block state with 0 or more copies if possible. own_Own block state with 0 or more shadow copies shadcopy (no copy blockstate) own_ Own block state with 0 or more snapshot copes. snapcopy (nocopy or shadow copy block state)

An example set of operands for the Control Flow (short instructionformat) instruction set are included in Table 108 below.

TABLE 108 [30:23] [22:17] [16:11] [10:5] [4:0] InstructionEncoding/Options FPA FPB FPC Predicate Fork encode[6:0], IP FP countsrc_pred fpobj [0] Join encode[6:0], IP FP count src_pred fpobj [0]Branch disp [5:0] src_pred BranchLink src_pred

The fork instruction set provides an instruction mechanism to create anew thread or micro-thread. Fork specifies the New Instruction Pointer(NIP) and new Frame Pointer for the newly created thread. At theconclusion of the fork instruction, the thread (or micro-thread) whichexecuted the instruction and the new thread (e.g. micro-thread) arerunning with fork_count (count) incremented by one. If the new FP has norelationship to the old FP, it may be considered a new thread, orotherwise a new micro-thread. The Fork instruction binary format can beexpressed as:

Fork Instruction (binary format) [30:24] [23] [22:17] [16:11] [10:5][4:0] where NIP NFP count Predicate

An example set of operands for the Fork instruction set are included inTables 109-113 below.

TABLE 109 where-Where fork join count can be stored Encoding SymbolDescription 0x0 frame Fork count can be stored directly on the frame.Faster, but only accessible to micro-threads within the same thread on asingle node 0x1 object Fork count can be stored within the object whichenables distributed operation.

TABLE 110 predicate-Predicate Description Specifies a single bitpredicate register. If the predicate value is true, the instructionexecutes, if false the instruction does not execute.

TABLE 111 NIP-New micro-thread Instruction Pointer Description Specifiesthe unsigned offset from the thread frame pointer to read the IP of thenewly spawned micro-thread. The IP can be a valid object meta-dataexpansion space address.

TABLE 112 New micro-thread Frame Pointer Description Specifies theunsigned offset from the thread frame pointer to read the FP of thenewly spawned micro-thread. The FP can be a valid object meta-dataexpansion space address.

TABLE 113 count-Fork count variable Description The fork_count variablekeeps track of the number of forks that have not been paired with joins.If the where options indicates frame, the count specifies the unsignedoffset from the thread frame pointer where fork_count can be located. Ifthe where option indicates object, the count specifies the unsignedoffset from the thread frame pointer to read the pointer to fork_count.

Join is the instruction mechanism to create a new thread ormicro-thread. The join instruction set enables a micro-thread to beretired. The join instruction decrements fork_count (count) andfork_count is greater than zero there is no further action. Iffork_count is zero, then this indicates the micro-thread executing thejoin is the last spawned micro-thread for this fork_count and executioncontinues at the next sequential instruction with the FP specified byFP. The Join instruction binary format can be expressed as:

[30:24] [23] [22:17] [16:11] [10:5] [4:0] where FP count Predicate

An example set of operands for the Join instruction set are included inTables 114-117 below.

TABLE 114 where-Where fork join count can be stored Encoding SymbolDescription 0x0 frame Fork count can be stored directly on the frame.Faster, but only accessible to micro-threads within the same thread on asingle node 0x1 object Fork count can be stored within the object whichenables distributed operation.

TABLE 115 predicate-Predicate Description Specifies a single bitpredicate register. If the predicate value is true, the instructionexecutes, if false the instruction does not execute.

TABLE 116 NFP-Post join Frame Pointer Description Specifies the unsignedoffset from the thread frame pointer to read the FP of the post joinmicro-thread. The FP can be a valid object meta-data expansion spaceaddress.

TABLE 117 count-Fork count variable Description The fork_count variablekeeps track of the number of forks that have not been paired with joins.If the where options indicates frame, the count specifies the unsignedoffset from the thread frame pointer where fork_count can be located. Ifthe where option indicates object, the count specifies the unsignedoffset from the thread frame pointer to read the pointer to fork_count.

The branch instruction set allows for branch and other conventionalinstructions to be added. The Branch instruction binary format can beexpressed as:

Branch Instruction (binary format) [30:24] [23] [22:17] [16:11] [10:5][4:0] Predicate

An example set of operands for the Execute (short instruction format)instruction set are included in Table 118 below

TABLE 118 Short Instruction Format-Execute [30:23] [22:17] [16:11][10:5] [4:0] Instruction Encoding/Options FPA FPB FPC Predicate Addencode[5:0],esize[1:0] srcA srcB dst src_pred Compareencode[5:0],esize[1:0] srcA srcB dpred src_pred

In the foregoing description, for the purposes of illustration, methodswere described in a particular order. It should be appreciated that inalternate embodiments, the methods may be performed in a different orderthan that described. It should also be appreciated that the methodsdescribed above may be performed by hardware components or may beembodied in sequences of machine-executable instructions, which may beused to cause a machine, such as a general-purpose or special-purposeprocessor or logic circuits programmed with the instructions to performthe methods. These machine-executable instructions may be stored on oneor more machine readable mediums, such as CD-ROMs or other type ofoptical disks, floppy diskettes, ROMs, RAMs, EPROMs, EEPROMs, magneticor optical cards, flash memory, or other types of machine-readablemediums suitable for storing electronic instructions. Alternatively, themethods may be performed by a combination of hardware and software.

While illustrative and presently preferred embodiments of the inventionhave been described in detail herein, it is to be understood that theinventive concepts may be otherwise variously embodied and employed, andthat the appended claims are intended to be construed to include suchvariations, except as limited by the prior art.

What is claimed is:
 1. A hardware-based processing node of a memoryfabric, the hardware-based processing node comprising: a memory modulecomprising a hardware component installed in the hardware-basedprocessing node, the memory module storing and managing one or morememory objects, wherein: each memory object is created natively withinthe memory module through an object name space of the memory fabricusing an instruction of an instruction set providing an object memoryfabric instruction model based on metadata defined for each memoryobject, each memory object is accessed by applications executing on thehardware-based processing node through the object name space of thememory fabric using a memory reference instruction of the instructionset and without additional, explicit Input/Output (I/O) instructions bythe applications, and each memory object is managed by the memory modulethrough the object name space of the memory fabric and the instructionset without distinction between persistent storage and temporary memoryand without distinction between local and remote location of memoryobjects on the memory fabric using the metadata defined for each memoryobject, according to the object memory fabric instruction model, andbased on one or more executable trigger instructions for each memoryobject defined in the metadata, wherein the metadata defining eachexecutable trigger instruction defines one or more pre-defined actionsto be performed on a per-block basis with respect to one or more datablocks and defines sequences of instructions, the sequences ofinstructions are executed and managed based on access of data of one ormore of the memory objects, wherein the metadata is local to the memoryobject and is within the memory object for which the executable triggerinstruction is defined.
 2. The hardware-based processing node of claim1, wherein the object memory fabric comprises a plurality ofhardware-based processing nodes, wherein each memory object and themetadata of each memory object are maintained on any one or more of theplurality of nodes in the object memory fabric, and wherein managing thememory objects according to the memory data flow model includesexecuting the sequences of instructions local to each memory object asthe memory objects are moved, split, or duplicated between nodes.
 3. Thehardware-based processing node of claim 1, wherein each of the sequencesof instructions has a corresponding thread state and wherein the threadstate for each of the sequences of instructions is stored in themetadata for the memory object.
 4. The hardware-based processing node ofclaim 2, wherein the sequences of instructions are further executed andmanaged based on actual dependencies of the memory objects.
 5. Thehardware-based processing node of claim 1, wherein the hardware-basedprocessing node comprises a Dual In-line Memory Module (DIMM) card. 6.The hardware-based processing node of claim 1, wherein thehardware-based processing node comprises a commodity server and whereinthe memory module comprises a Dual In-line Memory Module (DIMM) cardinstalled within the commodity server.
 7. The hardware-based processingnode of claim 6, further comprising a communication interface coupledwith the object memory fabric.
 8. The hardware-based processing node ofclaim 7, wherein the communication interface comprises a PeripheralComponent Interconnect Express (PCI-e) card.
 9. The hardware-basedprocessing node of claim 1, wherein the hardware-based processing nodecomprises a mobile computing device.
 10. The hardware-based processingnode of claim 1, wherein the hardware-based processing node comprises asingle chip.
 11. An object memory fabric comprising: a plurality ofhardware-based processing nodes, each hardware-based processing nodecomprising: one or more memory modules, each memory module comprising ahardware component installed in the hardware-based processing node, eachmemory module storing and managing a plurality of memory objects andcomprising an instruction set providing an object memory fabricinstruction model based on metadata defined for each memory object,wherein each memory object is created natively within the memory modulethrough an object name space of the object memory fabric using aninstruction of the instruction set, each memory object is accessed byapplications using a memory reference instruction of the instruction setand without additional, explicit Input/Output (I/O) instructions by theapplications, and each memory object is managed by the memory modulethrough the object name space of the object memory fabric and theinstruction set without distinction between permanent storage andtemporary memory and without distinction between local and remotelocation of memory objects on the memory fabric using the metadatadefined for each memory object, according to the object memory fabricinstruction model, and based on one or more executable triggerinstructions for each memory object defined in the metadata, wherein themetadata defining each executable trigger instruction defines one ormore pre-defined actions to be performed on a per-block basis withrespect to one or more data blocks and defines sequences ofinstructions, the sequences of instructions are executed and managedbased on access of data of one or more of the memory objects wherein themetadata is local to the memory object and is within the memory objectfor which the executable trigger instruction is defined, and a noderouter communicatively coupled with each of the one or more memorymodules of the node and adapted to route memory objects or portions ofmemory objects between the one or more memory modules of the node; andone or more inter-node routers communicatively coupled with each noderouter, wherein each of the plurality of nodes of the object memoryfabric is communicatively coupled with at least one of the inter-noderouters and adapted to route memory objects or portions of memoryobjects between the plurality of nodes.
 12. The object memory fabric ofclaim 11, wherein each memory object and the metadata of each memoryobject are maintained on any one or more of the plurality of nodes inthe object memory fabric and wherein managing the memory objectsaccording to the memory data flow model includes executing the sequencesof instructions local to each memory object as the memory objects aremoved, split, or duplicated between nodes.
 13. The object memory fabricof claim 11, wherein each of the sequences of instructions has acorresponding thread state and wherein the thread state for each of thesequences of instructions is stored in the metadata for the memoryobject.
 14. The object memory fabric of claim 11, wherein the sequencesof instructions are further executed and managed based on actualdependencies of the memory objects.
 15. The object memory fabric ofclaim 11, wherein the hardware-based processing node comprises a DualIn-line Memory Module (DIMM) card.
 16. The object memory fabric of claim11, wherein the hardware-based processing node comprises a commodityserver and wherein the memory module comprises a Dual In-line MemoryModule (DIMM) card installed within the commodity server.
 17. The objectmemory fabric of claim 16, further comprising a communication interfacecoupled with the object memory fabric.
 18. The object memory fabric ofclaim 17, wherein the communication interface comprises a PeripheralComponent Interconnect Express (PCI-e) card.
 19. The object memoryfabric of claim 11, wherein the hardware-based processing node comprisesa mobile computing device.
 20. The object memory fabric of claim 11,wherein the hardware-based processing node comprises a single chip. 21.A method for storing and managing one or more memory objects in anobject memory fabric, the method comprising: creating, through an objectname space of the object memory fabric each memory object nativelywithin a memory module of a hardware-based processing node of the objectmemory fabric based on instructions of an instruction set providing anobject memory fabric instruction model based on metadata defined foreach memory object; accessing, by one or more applications, each memoryobject through the object name space of the object memory fabric using amemory reference instruction of the instruction set and withoutadditional, explicit Input/Output (I/O) instructions by theapplications; and managing each memory object within the memory modulethrough the object name space of the object memory fabric and theinstruction set without distinction between permanent storage andtemporary memory and without distinction between local and remotelocation of memory objects on the memory fabric using a set of metadatadefined for each memory object, according to the object memory fabricinstruction model, and based on one or more executable triggerinstructions for each memory object defined in the metadata, wherein themetadata defining each executable trigger instruction defines one ormore pre-defined actions to be performed on a per-block basis withrespect to one or more data blocks and defines sequences ofinstructions, the sequences of instructions are executed and managedbased on access of data of one or more of the memory objects, whereinthe metadata is local to the memory object and is within the memoryobject for which the executable trigger instruction is defined.
 22. Themethod of claim 21, wherein the object memory fabric comprises aplurality of hardware-based processing nodes, wherein each memory objectand the metadata of each memory object are maintained on any one or moreof the plurality of nodes in the object memory fabric, and whereinmanaging the memory objects according to the memory data flow modelincludes executing the sequences of instructions local to each memoryobject as the memory objects are moved, split, or duplicated betweennodes.
 23. The method of claim 21, wherein each of the sequences ofinstructions has a corresponding thread state and wherein the threadstate for each of the sequences of instructions is stored in themetadata for the memory object.
 24. The method of claim 21, wherein thesequences of instructions are further executed and managed based onactual dependencies of the memory objects.